US9390268B1 - Software program identification based on program behavior - Google Patents

Software program identification based on program behavior Download PDF

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US9390268B1
US9390268B1 US14/818,271 US201514818271A US9390268B1 US 9390268 B1 US9390268 B1 US 9390268B1 US 201514818271 A US201514818271 A US 201514818271A US 9390268 B1 US9390268 B1 US 9390268B1
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software application
sequence
signature
determining
application instance
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Paul Michael Martini
Peter Anthony Martini
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Iboss Inc
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1441—Countermeasures against malicious traffic
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55—Detecting local intrusion or implementing counter-measures
    • G06F21/56—Computer malware detection or handling, e.g. anti-virus arrangements
    • G06F21/566—Dynamic detection, i.e. detection performed at run-time, e.g. emulation, suspicious activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/52—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity ; Preventing unwanted data erasure; Buffer overflow
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55—Detecting local intrusion or implementing counter-measures
    • G06F21/56—Computer malware detection or handling, e.g. anti-virus arrangements
    • G06F21/562—Static detection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1416—Event detection, e.g. attack signature detection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1433—Vulnerability analysis
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1441—Countermeasures against malicious traffic
    • H04L63/145—Countermeasures against malicious traffic the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/03—Indexing scheme relating to G06F21/50, monitoring users, programs or devices to maintain the integrity of platforms
    • G06F2221/033—Test or assess software

Definitions

  • the present document relates to computer security.
  • Malicious software includes software programs that can or does perform actions that can harm or work against the interest of a user or computer system owner. Examples of such software include “adware” programs that monitor user behavior and present ads to the user, “spyware” programs that monitor user behavior, and computer viruses that may perform various malicious actions, including deleting files, and taking control of the user's computer to perform unauthorized operations.
  • All software applications whether malicious or not, perform various operations during execution, such as, for example, accessing the file system, opening network ports, changing values stored in memory, and other operations.
  • a method is performed by data processing apparatus.
  • the method includes identifying application signatures each representing one or more software applications, each application signature including a total score threshold and one or more operation sequences each including a plurality of sequence operations, wherein each sequence listing is associated with a sequence score.
  • the method further includes monitoring operations performed by a software application instance executed by a computing device.
  • the method further includes determining that a first operation performed by the software application instance matches a first sequence operation included in a particular sequence listing for a particular application signature.
  • the method further includes after determining that the first operation performed by the software application instance matches the first sequence operation, determining that a second operation performed by the software application instance matches a second sequence operation included in the particular sequence listing.
  • the method further includes in response to determining that the second operation matches the second sequence operation, determining that each of the plurality of sequence operations for the particular sequence listing has been observed for the software application instance.
  • the method further includes in response to determining that each of the plurality of sequence operations for the particular sequence listing has been observed, adding the sequence score to a total score for the software application instance.
  • the method further includes in response to adding the sequence score to the total score, determining that the total score for the software application instance is greater than or equal to the total score threshold for the particular application signature.
  • the method further includes in response to determining that the total score is greater than or equal to the total score threshold, classifying the software application instance as the software application represented by the particular application signature.
  • Implementations can include any, all, or none of the following features.
  • Each application signature includes operations each associated with a match score.
  • the method further comprises determining that the first particular operation performed by the software application instance matches an operation included in the particular application signature; and in response to determining that the first particular operation matches the operation included in the particular application signature, adding a match score associated with the particular operation to the total score associated with the software application instance.
  • the sequence listing includes a particular order for the plurality of sequence operations, the first sequence operation being in a first position in the particular order, and the second sequence operation being in a final position in the particular order.
  • Monitoring operations performed by a software application instance executed by a computing device comprises performing static analysis of one or more attributes of the software application instance.
  • Performing static analysis of one or more attributes of the software application instance comprises determining if the one or more attributes match a preconfigured value in an application signature.
  • the one or more attributes includes at least one of the group consisting of a Secure Hash Algorithm (SHA) value, an MD5 value, and a program name.
  • the method further comprising performing, responsive to classifying the software application instance as the software application represented by the particular application signature, a configured action associated with the particular application signature.
  • the configured action is selected from a plurality of actions based on a determination of a type of the computing device.
  • the determined type is a network security device; and the configured action comprises terminating network traffic with a server that served the particular software application.
  • the determined type is a client device that resides on a network; and the configured action comprises powering down the client device.
  • the configured action comprises presenting, responsive to classifying the software application instance as the particular software application represented by the particular application signature, a report identifying i) the particular software application and ii) the particular application signature.
  • the report further comprises a human-readable description of the particular application signature.
  • the method further comprising generating the report from a template document that includes at least an application-related fillable field and a signature-related fillable field using data associated with the particular application signature.
  • the software application instance executed by a computing device is executed on a client device.
  • the software application instance executed by a computing device is executed in a sandbox environment.
  • Each application signature represents a particular class of software application include the one or more software applications.
  • the method further comprising: monitoring operations performed by a second software application instance executed by the computing device; determining that a particular operation performed by the second software application instance matches an operation included in the particular application signature; in response to determining that the particular operation matches the operation included in the particular application signature, adding a match score associated with the particular operation to a total score associated with the second software application instance; in response to adding the match score to the total score, determining that the total score for the software application instance is less than the total score threshold for the particular application signature; and in response to determining that the total score is greater than or equal to the total score threshold, allowing the second software application instance to continue execution without classifying it as the particular software application.
  • System and computer storage media encoded with computer program instructions are providing for performing similar operations.
  • FIGS. 1A, 1B, and 1C are block diagrams of example computer systems in which the present techniques for identifying malicious application instances may be implemented.
  • FIG. 2 is a swim-lane diagram of an example process for identifying malicious application instances.
  • FIGS. 3A and 3B are block diagrams of example computing sandbox techniques.
  • FIG. 4 is a flowchart of an example process for identifying malicious application instances.
  • FIG. 5 is a flowchart of an example process for identifying malicious application instances.
  • FIG. 6 is a schematic diagram that shows an example of a computing device and a mobile computing device.
  • Application instances e.g., software programs, data files
  • executing on a computer system may include malicious instructions, such as viruses, macros, scripts, or other instructions embedded in the object that perform malicious operations without the user's knowledge.
  • Security programs such as anti-virus software generally scan a computer for known malicious application instances (such as by filename or based on a file signature of a virus or other malicious program), or monitor activity on the computer to detect such objects.
  • Some malicious programs may include functionality to evade such security programs, such as by changing their own instructions or data footprint so as not to be recognized by a scan (a technique known as polymorphism), or by attacking the security software itself. Such security software may therefore be ineffective in some cases.
  • the present application describes techniques for identifying software applications as possibly malicious by detecting objects that perform operations matching an ordered list of operations.
  • a framework is described in which signatures can be generated to represent software applications based on the operations they perform.
  • the signatures may include ordered lists of operations known or suspected to be performed by the represented software application.
  • Executing software application instances may then be monitored to identify operations performed by the instances that match operations in the application signatures. If a software application instance requests a particular sequence of operations included in a particular application signature, a match score associated with the particular operations may be added to a total score for the software application instance. In some cases, the total score represents a likelihood that the software application instance is an instance of the software application represented by the application signature.
  • the particular application signature may also include a total score threshold indicating.
  • the software application may be classified as an instance of the software application represented by the application signature.
  • configured actions associated with the application signature may be performed, such as, for example, terminating the software application instance, deleting the software application from which the instance originated, quarantining the software application instance, alerting an administrator, updating the application signature based on information collected about the software application instance, or other actions.
  • Some or all of these signatures may be used in different computer devices, providing a networked client device with a layered protection. For example, a network security device may identify a software application entering the network. Before passing the software application to the client device, the network security device may test the software application in a sandbox environment. If this software application does not get marked as risky by the network security device, the software application can be routed to the client device. At the client device, the execution of the software application can be monitored using some or all of the same signatures that were used in the sandbox.
  • the application signatures may be used to identify software applications other than malicious ones. For example, an instance of a word processing program might be identified as that program based on the instance writing to a particular directory in the file system, based on registry keys it accesses during execution, display operations it requests during execution, or other operations.
  • the techniques described herein may provide the following advantages.
  • the present techniques may be less affected by standard evasion techniques, such as polymorphism, used by viruses and other malicious programs, as the present techniques do not rely solely on detecting a program signature or other attribute of the malicious program.
  • standard evasion techniques such as polymorphism
  • a redundant protection scheme can provide computer devices with protection from context-dependent threats.
  • Administrators can reuse signatures created for a virtual environment on live network environments without having to re-create a different set of signatures, saving time and making the signatures more effective as they may have already been tested in a virtual environment.
  • Reports of malicious software applications can be generated to include information about what kind of signatures a software application matches and why a particular total score was calculated, giving network administrators or other users information needed to properly handle the risky application.
  • the set of signatures used by my controlled by an administrated that can add, remove, and/or modify signatures as needed in a particular application. The administrator may also configure signatures to manage a particular threat.
  • a network being attacked by a custom advanced persistent threat can have signatures custom-created by the network administrator to defend against that advanced persistent threat.
  • the network administrator can create these rules without the inclusion of a third party (e.g., a security researcher or device vendor), thus providing the network administrator with the potential for a faster reaction time and the ability to properly manage disclosure of the attack.
  • the signatures can include environment-specific tests and/or actions that are only applied in the applicable environment. For example, a signature may specify that a machine should power down when malware designed to encrypt the user's files is found.
  • FIGS. 1A and 1B are block diagrams of example environments in which the present techniques for identifying malicious application instances may be implemented.
  • the computer network 100 includes a network gateway 102 that includes a sandbox environment for running unknown software. Also shown in the network 100 is a client device 106 , which represents any appropriate computing device capable of browsing resources outside of the network 100 . While not shown for clarity's sake, the network 100 can include other elements including, but not limited to, wireless and/or wired access points, file and/or application servers, routers, and network cables, as well as additional client devices 106 and/or network gateways 102 .
  • the network 100 can be configured to route some or all of the messages addressed outside the network 100 to the network gateway 102 .
  • the network gateway 102 can inspect the messages and, optionally, modify or drop some messages.
  • the network gateway 102 may be configured to prevent traffic from a particular class of application (e.g., chat, files sharing).
  • the network gateway 102 may also be configured to intercept messages intended for a recipient outside of the network 100 and reply directly.
  • the network 100 can be configured to route some or all of the messages addressed into the network 100 through the network gateway 102 .
  • the network gateway 102 can inspect the messages and, optionally, modify or drop some messages.
  • the network gateway 102 may be configured to prevent traffic from a particular class of application (e.g., chat, files sharing).
  • the network gateway 102 may also be configured to intercept messages intended for a recipient inside of the network 100 and reply directly.
  • the network gateway 102 may intercept some traffic addressed to recipients inside the network 100 , for example to enforce security or other network policies. For example, one or more messages that contain application instances (e.g., executable binary instructions, interpretable scripts, or the like) that are addressed to a recipient in the network 100 can be received by the network gateway 102 . Instead of routing the one or more messages, the network gateway 102 may instead test the application instance to determine if it is likely to be malicious. If it is determined not likely to be malicious, the network gateway 102 may then route the message or message on their way to the addressed recipient.
  • application instances e.g., executable binary instructions, interpretable scripts, or the like
  • the network gateway 102 may take an appropriate action such as deleting the software, serving a webpage to the intended recipient indicating that the application instance was found to be malicious, or holding the software in quarantine of further testing or analysis. Examples of determining malicious application instances are described below.
  • the client device 106 generates a request message 108 addressed to a resource hosted on a server 104 .
  • This request may be, for example, a hypertext transfer protocol (HTTP) GET message that includes the universal resource locator (URL) of the server 104 or a resource hosted on the server 104 .
  • HTTP hypertext transfer protocol
  • the network gateway 102 may, possibly after examining the request 108 for any applicable security or network policies, route the request 108 to the server 104 .
  • the server 104 can receive the request 108 and determine that the server 104 should reply by serving the requested resource. To do so, the server 104 can create a response 110 that includes the requested resource. The server 104 can send this response 110 to the client device 106 . To reach the client device 106 , the response 110 can be routed through the network gateway 102 . Instead of routing the response 110 to the client device 106 , the network gateway 102 can intercept the response 110 to determine 114 if the response 110 complies with security or other network policies of the network 100 .
  • the network gateway 102 may include rules 103 that define a security policies of the network.
  • One such policy may specify that particular application instances should be tested in a sandbox.
  • a sandbox is a controlled execution environment where, for example, an unknown application instance can be run without allowing the application instance to access critical components of a computing device.
  • the network gateway 102 can initiate a sandbox 112 and run the application instance attached to the reply 110 .
  • the sandbox 112 can allow the application instance to run, install, or open it using an associated application, such as using a word processing program to open a text document.
  • the sandbox 112 can apply one or more tests to the application instance to determine if the application instance contains malicious functionality or is likely to contain malicious functionality. For example, the sandbox 112 may execute the application instance for a period of time, and compare the behavior and features of the running instance against a suite of signatures designed to identify potentially malicious or unwanted software applications. Examples of these signatures is described below.
  • the network gateway 102 may take an appropriate action. These actions may be specified by the rules 103 . For example, the network gateway 102 may drop any communications with the server 104 , may quarantine the received application instance, and/or may subject the application instance to additional testing. This additional testing may, for example, take longer than the initial tests used to determine the application instance is malicious. In some cases, the additional testing may be more accurate, but at the cost of processing time.
  • a webpage or other message may be served to the client device 106 informing the client device 106 that the reply 110 has been blocked. If the application instance is found to be low-risk or found not to contain malicious behavior, the reply 110 may be sent to the client device.
  • the network 130 differs from the network 100 of FIG. 1A at least in that the client device 106 hosts the sandbox 112 instead of the network gateway 102 hosting the sandbox 112 .
  • both the network gateway 102 and the client device 106 may host their own sandboxes 112 .
  • Hosting the sandbox at the client devices 106 instead of the network gateway 102 may have a number of implications for the computers systems. For example, by hosting the sandbox 112 at the only network gateway 102 , or all network gateways if a network has more than one, a network administrator can ensure that all traffic into the network can be subject to sandbox-based analysis. By hosting sandboxes at each client device 106 , different sandboxes with different rules may be used by client devices of different types. For example, a server hosting customer payment data may have a more rigorous testing scheme than user workstation computers.
  • the network administrator may only be able to configure a sandbox 112 at the network gateway 102 and the client device 106 owners may only be able to configure a sandbox 112 at their own client devices 106 .
  • the client device 106 While the client device 106 is shown hosting the sandbox 112 to run the resource, the use of a sandbox is not required.
  • the client device 106 may host one or more sandboxes and run the resource natively, or may not host any sandboxes.
  • FIG. 1C shows an example of a computer 150 that monitors application instances.
  • the computer 150 includes an operating system 152 that hosts an application monitor 154 , an executable 156 , a document viewer 158 displaying a file 160 and a virtual machine 162 running a script 164 . While not shown for clarity's sake, the computer 150 can include other elements including, but not limited to, input and output components, networking components, and other hardware and software.
  • the computer 150 can include any type of computer system that can execute an application instance. Examples include, but are not limited to, desktop or laptop computers, server systems, mobile computing devices, or embedded computing devices (e.g., controllers in ‘smart’ appliances, automotive computing systems).
  • the computer 150 includes and operating system 152 , or other similar system, to host running application, provide those applications with an interface to the computer 150 , to manage communications and storage, and for other purposes.
  • An application monitor 154 can run in the operating system, and/or may be a part of the operating system 152 .
  • the application monitor 154 may be configured to identify an execution of a application instance by the computer 150 .
  • the execution of a application instance can include, but is not limited to, the executable file 156 being executed, the file 160 being opened or used by the document viewer 158 , and the script 164 running in the virtual machine 162 .
  • the application monitor 154 can monitor the activities of the executing application instance. For example, the application monitor 154 may monitor the system calls of the executable 156 to check for an indication of malicious behavior.
  • One type of malicious behavior includes an application performing sensitive actions before interacting with a user of the computer 150 .
  • a normally functioning application will often draw a graphical user interface and present the interface to the user before accessing sensitive portions of the operating system 152 .
  • a malicious piece of adware may, instead of interacting with the user, install plug-ins to the user's web browser redirecting traffic to a network resource associated with the adware in order to monitor the user's web traffic.
  • the application monitor 154 determines that the application instance has requested a sensitive action before interacting with a user of the computer 150 , the application monitor can classify, or cause another element to classify, the running application instance as a malicious application instance. For example, the application monitor 154 may report to security software on the computer 150 (not shown) that the executable 156 has written data outside the executable 156 's directory before interacting with the user. The security software may use this as one signal to determine if the executable 156 is to be classified as malicious. For example, if the executable 156 is on a whitelist of known-good application, the executable 156 may be allowed to run as normal.
  • the security software may delete, isolate in a sandbox, or otherwise handle the executable 156 in a way that protects the computer 150 .
  • the network gateway may test an incoming software application against a set of signatures, and then the client device 106 or 150 may test the incoming software again.
  • Such a configuration may provide a computer device with defense in depth through redundant protection against malicious applications. For example, some if a sandbox test performed by a network security device tests a software application and determines that it is not a malicious application, the client system can still test the software application an additional time. This may be useful, for example, in cases where a software application displays different behavior in different environments.
  • the software application to be tested may not be an incoming software application.
  • the client device 106 or 150 may be configured to monitor the behavior of some, any, or all application running natively or in managed environments (e.g. sandboxes).
  • component of the operating system or an installable security application may perform the testing described in this document on all running applications, applications lacking known signed certificates, or a sample (random or otherwise) of software application instances.
  • a Trojan program e.g., a software application including a malicious payload
  • a network security device e.g., a router, a firewall, or other network attached device
  • the Trojan Program may act like an innocuous video game.
  • the network security device may calculate a total score based on the behavior of an instance of the Trojan program that does not classify it as the Trojan program.
  • the network security device may then route the Trojan program to the client device that requested it.
  • the Trojan program may attempt to deploy its malicious payload.
  • the client device may detect the behavior of the malicious payload upon deployment, classify the instance as the Trojan program, and take appropriate action. For example, the client application may terminate the Trojan program and alert a network administrator.
  • malware There are other types of application that may be configured to behave differently in different environments. For example, some malware is known to sleep in virtual environments and activate outside of virtual environments. A “spearfishing attack” may be configured to only deploy if a particular user or device configuration is found. An unwanted application plug-in (e.g., bundled into another program's installer application) may only install if the target application is found. Testing in both the virtual and non-virtual environments may be used to successfully identify any of these types of attacks, as well as other types of advanced persistent threats, advanced evasive threats, and advanced evasive malware.
  • a “spearfishing attack” may be configured to only deploy if a particular user or device configuration is found.
  • An unwanted application plug-in e.g., bundled into another program's installer application
  • Testing in both the virtual and non-virtual environments may be used to successfully identify any of these types of attacks, as well as other types of advanced persistent threats, advanced evasive threats, and advanced evasive malware.
  • each device may use the same, or some of the same, signatures to test the software application.
  • a set of signatures may be developed to detect a particular unwanted toolbar application.
  • These signatures may be used in dynamic tests such as monitoring the user preferences of a web browser and static testing such as examining the toolbar application to see if it contains a class known or believed to be common to unwanted toolbars.
  • These signatures may be used by any kind of computing device (e.g., a network computing device, a client device, a device hosting a sandbox) monitoring the execution of a software application.
  • some but not all of the devices may use different rules, even if those devices are all administered by the same organization.
  • a suite of sandbox-specific signatures crafted to catch behavior of applications attempting to escape a sandbox.
  • Example behaviors include, but are not limited to return-oriented programming, writing to memory locations outside of a permitted range, and attempting to escalate execution privileges.
  • Devices that run applications in a sandbox environment may be given these signature while, optionally, devices that don't run applications in a sandbox may not.
  • Other suites of signatures like this can include, but are not limited to, operating system specific signatures, hardware specific signatures, or user specific signatures.
  • devices may also use universal suites of signatures that can be use universally (e.g. for every device under a particular administration, on a network, or otherwise logically grouped).
  • the signatures can have associated actions.
  • a file defining a signature may identify, reference, or otherwise associate the signature with one or more action. These actions might include, for example, generating a report from a template to describe the type of software application identified, closing a network communication channel, deleting the software application, terminating the software application's running instance, or powering down the device executing the software application.
  • the action may be conditional based on the type of device running the test. For example, a particular or pair of signatures may specify that a network security device be configured to terminate a client's communication with a server, while a client device be configured to shut down.
  • the signature may also include universal actions to be performed without regard to the device running the test. For example, a reporting action may be specified as universal such that any detection by any device results in report generation.
  • Reports when a signature is matched may be programmatically generated. In some cases, this generation may be automatic—that is, without specific user input to cause the report to be generated.
  • One process for generating this report is to create a copy of a document template (e.g. of a webpage, of an email, of a text message) and to populate fields of that template with information about the signature, the environment, the application, etc.
  • This report may be logged and/or transmitted, for example to a network administrator tasked with protecting a network and/or to a security researcher tasked with identifying trends in the computer security field.
  • the number of times that a software application is tested may dependent on the configuration of the network or networks to which a client device is connected.
  • a client device may reside on a network protected with a network security device that performs the testing described in this document. While on that network, the client device may be protected by two layers of security—one layer being the testing by the network security device and one layer being the testing performed by the client itself.
  • That client device may leave the network and join another network (e.g., a user takes their laptop from their school to a coffee shop).
  • This new network may not be configured to provide this testing.
  • this same client is now protected by only a single layer—the testing performed by the client itself.
  • VPN Virtual Private Network
  • Some VPNs are configured such that general web browsing is routed through the virtual network before reaching the client.
  • the client may or may not be protected by another layer of protection depending on if the VPN is configured to perform the testing described. This usage may be repeated for any sort of technologically appropriate overlay network.
  • Signatures may be available for user inspection, creation, an editing.
  • a suite of signatures may be a collection of files stored by a computing device (e.g., in the rules 103 ) or otherwise accessible to the computing device. These signature files may be in a standard or custom file format that a user may be able to view and/or edit in a human-readable form.
  • One such form is a text file (e.g., an Extensible Markup Language (XML), JavaScript Object Notation (JSON), or other file) containing regular expressions (regexes) or other Boolean matching rules.
  • XML Extensible Markup Language
  • JSON JavaScript Object Notation
  • regular expressions regular expressions
  • Boolean matching rules e.gexes
  • signatures may be created by a variety of users, including but not limited to, network administrators, the users of a single client device, security professionals and device vendors.
  • static testing includes the testing of a static portion of a software application or testing of the application without the need to run the software application.
  • static testing include, but are not limited to, examination of a file, comparison of a hash of the software application (e.g., Secure Hash Algorithm (SHA), MD5), identification of a pseudorandom number in the software application (e.g., as a registry value), or the presence or absence of a particular software component (e.g., a cryptographic library and/or an opaque application instance).
  • SHA Secure Hash Algorithm
  • dynamic testing includes observations made while an instance of the software application is executing.
  • examples of dynamic testing include, but are not limited to, examination of system calls by the software application, documenting data written to memory, and monitoring network communications made by the software application.
  • dynamic testing can include identifying if the software application performs actions that match an ordered sequence of signatures.
  • a signature file may be configured to test if an application writes a value to the registry, accesses memory outside of a local directory, and then initiates a network query, in that order.
  • a test suite of signatures can be configured to include a list of categories, each represented for example by one text file.
  • Each category may include, for example, configuration data and a list of signatures.
  • the configuration data may include, for example, variable values set for a particular category.
  • the list of signatures may be a list of regular expressions (regexes) or other Boolean matching rules.
  • a regex are a sequence of characters that forms a search pattern, mainly for use in pattern matching with strings, or string matching.
  • a weight may be assigned that may indicate, for example, how dispositive a rule is. For example, if a rule is very likely to be dispositive to determining that a software application fits a particular profile, the weight may be higher than for a rule that is only slightly indicative that a software application fits a particular profile.
  • each matching signature can be assigned a mark and a summation of all marked signatures weights may be made. Then, the number of marks and/or the summarized weights may be compared to one or more threshold values to determine a risk metric for the software application. These threshold values may be defined, for example, in the configuration data of the category.
  • the score may then be augmented if the matches occur based on a particular ordered sequence.
  • Each sequence identifies a particular order of operations that a tested piece of software may execute, with or without other operations in between.
  • a sequence weight can be applied to the summation of the signature marks in order to increase or decrease the weight. For example, it may be determined that software that accesses a registry, then modifies system libraries is likely malicious. In such a situation, a signature may exist to monitor for access of the registry and another for modifications to the library. If both of those actions are performed out of order, the weight for that application would be the sum of those two signatures. If, however, the actions are performed in the specified order, the weight can be modified with an additional weight associated with the order. Since it was determined that performance of those actions in order is more indicative of problematic software, software with those actions in order result in a greater final weight.
  • the ordered sequence may be set to a ‘strict ordering’ or not.
  • ‘strict ordering’ sequences the ordered sequences must be performed in order, without other operations being performed in between elements of the sequence.
  • sequences that are not identified as strict other operations may be performed in between the operations of the sequence and a match may still be found.
  • a sequence identifies an OS system call followed by a network communication and an application instance calls the OS system call, writes data to memory, and then begins a network communication. If the sequence is set as strict, this would not be a match. If the sequence is not set to strict, this would be a match.
  • a single threshold may be used to classify an instance of a software application as either risky or not, of a particular class of software or not, etc.
  • Multiple thresholds may be used to place the instance of a software application into a multi-band metric. For example, a software application instance is tested against a particular category, and the result is two marks and a nineteen weight.
  • This category is created in a single .JSON text file.
  • the category of signatures includes configuration at the beginning of the file, followed by a list of signatures.
  • Each of the signatures has an associated “sequenceOrder” value.
  • sequenceOrder For positive integer values of “sequenceOrder” the signatures must be matched in the order of the values.
  • sequenceOrder values of ⁇ 1, a sequence could be matched in any order.
  • matchPattern “*lock*”, //pcre regular expression “matchLowercase”: true, //convert the sample to lower- case before applying match patterns// “operationType”: [“any”, “present”, “injected”, “created”, “terminated”, “shellcommand”], “parentMatchPattern”: “*lock*”, //parent process name “parentMatchLowercase”: true, “sequenceOrder”: ⁇ 1 ⁇ ], “staticSamples”: [ ⁇ “signatureTag”: “the file sample itself”, //arbitrary name “score”: 1, //adds to the match_total_score “matchType”: “magic_literal”, //magic_literal, trid, file_content, memory_map “matchPattern”: “*eicar*”, //pcre for magic_literal/trid.
  • matchPattern “*google.com*”, //pcre regular expression “matchLowercase”: true, //convert the sample to lowercase before applying match patterns “sequenceOrder”: ⁇ 1 ⁇ , ⁇ “signatureTag”:“ip network match”, “score”: 1, //adds to the match_total_score “protocol”: “ip”, //dns, tcp, udp, http, ip, any “matchType”: “source_ip”, //source_ip, destination_ip “matchPattern”: “74.125.*”, //pcre regular expression “sequenceOrder”: ⁇ 1 ⁇ , ⁇ “signatureTag”:“tcp network match”, “score”: 1, //adds to the match_total_score “protocol”: “tcp”, //dns, tcp, udp, http, ip, any “matchType”: “source port”, //source__
  • This category is created in a single .JSON text file. As shown, the category of signatures includes configuration at the beginning of the file, followed by a list of signatures. Each signature specifies a Boolean test an associated tags used for the test, in reporting the results of the signature, etc. Although this particular example is shown, other formats are possible.
  • matchPattern “*lock*”, //pcre regular expression “matchLowercase”: true, //convert the sample to lowercase before applying match patterns// “operationType”: [“any”, “present”, “injected”, “created”, “terminated”, “shellcommand”], “parentMatchPattern”: “*lock*”, //parent process name “parentMatchLowercase”: true ⁇ ], “staticSamples”: [ ⁇ “signatureTag”: “the file sample itself”, //arbitrary name “score”: 1, //adds to the match_total_score “matchType”: “magic_literal”, //magic_literal, trid, file_content, memory_map “matchPattern”: “*eicar*”, //pcre for magic_literal/trid.
  • matchPattern “*google.com*”, //pcre regular expression “matchLowercase”: true //convert the sample to lowercase before applying match patterns ⁇ , ⁇ “signatureTag”:“ip network match”, “score”: 1, //adds to the match_total_score “protocol”: “ip”, //dns, tcp, udp, http, ip, any “matchType”: “source_ip”, //source_ip, destination_ip “matchPattern”: “74.125.*” //pcre regular expression ⁇ , ⁇ “signatureTag”:“tcp network match”, “score”: 1, //adds to the match_total_score “protocol”: “tcp”, //dns, tcp, udp, http, ip, any “matchType”: “source_port”, //source_port, destination_port “ports”: [“80”, “25-30”] //single ports
  • FIG. 2 is a swim-lane diagram of an example process 200 for testing software for signs of risk.
  • the process 200 is being described with reference to the elements shown in FIGS. 1A and 1C .
  • other components including but not limited to those shown in FIG. 1B , may be used to perform the process 200 or similar processes.
  • the computer 150 requests 202 a software application.
  • the server 104 serves 204 the software application.
  • a user on the computer 150 sends a request to the server 104 (e.g., a hypertext transfer protocol (HTTP) GET request, a file transfer protocol (FTP) RETR command) to serve a software application.
  • HTTP hypertext transfer protocol
  • FTP file transfer protocol
  • the server 104 can marshal a copy of the software application and send the software application to the computer 150 in an appropriate reply message.
  • the network gateway 102 intercepts 206 the software application.
  • the network gateway 102 can monitor traffic addressed to and from the computer 150 and intercept the traffic containing the software application.
  • the network gateway 102 runs 208 an instance of the software application in the sandbox 112 and monitors 210 the execution of the software application in the sandbox 112 .
  • the network gateway 102 can run a copy of the intercepted software application in a security sandbox on the same or different hardware. While the instance of the software application runs, the network gateway 102 , or another appropriate device, can monitor the instance of the software application.
  • This monitoring can include comparing the software application instance to one or more signatures that define tests to determine if the software application fits a profile of software that should be excluded from computers on the network (e.g., matching the software to a list of signatures and a group of ordered lists of signatures).
  • the network gateway 102 performs a configured action 214 . For example, if the software application instance matches one or more signatures, or if the number or weight of matching signatures is greater than one or more threshold values, the network gateway 102 can perform one or more configured actions. These actions can include actions specified by the signatures or other files, or may be performed if any software application instance fails a test. These actions include, but are not limited to creating an alert, generating a log entry, blocking the software application, and/or passing the software application to the computer 150 .
  • the particular signature tripped may be configured to identify software applications that are desired. For example, consider an example of a corporate network that deploys a browser toolbar to the client machines on the network. This corporation's toolbar may be the only desired toolbar and all other toolbars should be excluded. A set of signatures that is configured to identify any toolbar would match both undesired and the desired toolbar.
  • the corporate network's administrator may make a set of signatures with negative weight targeting the corporate toolbar only (e.g., by matching a publisher certificate signed by the corporation).
  • the signatures that identify any toolbar may generate a positive weight offset by the negative weight of the targeted corporate-toolbar signatures.
  • the corporate network's administrator may make a category of signatures to identify the corporate toolbar, and, if the category finds a match, pass the software application to its intended recipient instead of blocking it or generating an alert.
  • the network gateway 102 returns the software application to the computer 150 at 216 . For example, if the software application's instance does not exhibit any features or behavior that identify the software as unwanted, the network gateway 102 can pass the software application to the computer 150
  • the computer 150 executes the software application and performs a test 220 on the executing instance of the software application.
  • the computer can run, interpret, load, or otherwise execute the software application. This execution may be monitored by the computer 150 , using the same, similar, or different rules than the network gateway 102 used.
  • the computer 150 performs the configured action 224 .
  • the computer 150 may take the same, similar, or different action than those of the network gateway 102 , depending on the configuration.
  • FIGS. 3A and 3B are block diagrams of example computing sandbox techniques.
  • a computer system 300 hosts a sandbox for running applications.
  • the computer system 300 includes hardware 302 , an operating system 304 running on the hardware 302 , and a sandbox 306 hosted by the operating system.
  • the hardware 302 includes the collection of physical elements of the computer system 300 .
  • the hardware 302 shown includes a processor 308 , memory 310 , and I/O devices 312 , though other configurations are possible.
  • the processor 308 is one or more computing processors capable of carrying out computing instructions.
  • the memory 310 includes long term storage (e.g., hard disk) and system memory (e.g., Random Access Memory (RAM) components).
  • the I/O devices 312 include hardware for input and output, such as for communicating with users and other computer systems.
  • Example I/O devices include, but are not limited to, keyboards, pointer devices, speakers, and network connections.
  • the operating system 304 may run on the computer hardware 302 .
  • the operating system is software that manages computer hardware and software resources and provides common services for computer programs.
  • the operating system includes system functions 314 . These system functions 314 can provide access to the computer hardware, or can provide a single interface for common functions.
  • Example system functions 314 include, but are not limited to, functions for establishing a service or daemon, reading an environment variable, and turning the computer system 300 off.
  • Memory allocation functions 316 allow a caller to allocate, de-allocate, read, write, lock, or otherwise interact with the memory 310 .
  • I/O Functions 318 can allow a caller to interact with I/O devices 312 .
  • Example I/O functions include, but are not limited to, functions for establishing network sockets, writing to display buffers, and reading input from pointer devices.
  • the operating system can host one or more application. These application include, but are not limited to, web browsers, document editors, web servers, video games, and other applications which may or may not have user-facing components. Additionally, the operating system 304 can host one or more other execution environments. One such execution environment is the sandbox 306 .
  • the sandbox 306 includes an execution environment for hosting one or more applications, including sandboxed applications 328 and 330 .
  • the sandboxed applications 328 and 330 may be permitted only to access system hooks 322 , memory hooks 324 , and I/O hooks 326 .
  • the system hooks 322 , memory hooks 324 , and I/O hooks 326 may have the same interfaces as the system functions 314 , memory allocation 316 , and I/O functions 318 and may imitate the interfaces of the operation system 304 .
  • the system hooks 322 , memory hooks 324 , and I/O hooks 326 may have a different interface or interfaces.
  • a communication manager 320 in the sandbox 306 may examine the call and determine how to respond to the call, if at all.
  • the call may be passed to a corresponding system function 314 , memory allocation 316 , or I/O function 318 .
  • the communication manager 320 may generate a response without communicating with the operating system. Additionally, the communication manager 320 can perform additional functions related to these calls.
  • Calls may be logged and/or analyzed to determine, for example, if the call attempts to perform a restricted action or a permitted action on a restricted resource.
  • the communication manager 320 may treat calls from each application 328 and 330 differently or the same, depending on the configuration.
  • the sandbox 306 may be used for one or more of a variety of functions. In one use, the sandbox 306 is used to provide security to the computer system 300 while the sandboxed application 328 and 330 are run. For example, the sandboxed application 328 and 330 may be from an untrusted source or may be known to have malicious behavior. By monitoring communications between the sandboxed application 328 and 330 and the operating system 304 , the communication manager 320 can prevent the sandboxed application 328 and 330 from having an undesirable effect on the operating system 304 .
  • the sandbox may be part of a virtual machine.
  • Virtual machines are logical recreations of a full or partial computing system hosted on a real computer system like the computer system 300 . Virtual machines may be used in some cases to interpret scripting language application, allowing the scripting language to be platform agnostic. Additionally or alternatively, virtual machines may be used to provision a single computer system 300 to multiple uses. For example, if the computer system 300 is a networked server computer, multiple virtual servers may be provisioned on the single real server.
  • the sandbox may be part of an emulator.
  • Emulators are a specific type of virtual machine where the system hooks 322 , memory hooks 324 and I/O hooks 326 provide a different interface than what is provided by the operating system 304 .
  • a virtual machine emulating a mobile computing device may be used on a desktop computing device running a different operating system. This emulated mobile computing device may be to test an application that is developed on the desktop device but targeted for use in the mobile device.
  • a sandbox modifier 350 replaces instructions in an application 352 to create a sandboxed application 354 .
  • This replacement process may be used in addition to or in the alternative to the sandbox 306 previously described.
  • a computer system can use the sandbox modifier 350 to identify and replace some of the instructions of the application 352 .
  • the instructions replaced include binary computer instructions.
  • the instructions replaced include scripting instructions.
  • the sandbox modifier 350 can inspect the application 352 and identify any instructions that, for example, include calls to the operating system or include calls to sensitive computing resources. In the example shown, the sandbox modifier 350 identifies two instructions, “I/O instruction4” and “Sensitive Instruction5.” Before loading the application 352 , the sandbox modifier can modify the application 352 by replacing these two instructions with calls to, for example, a sandbox interface that includes hooks for function calls to the operating system. By performing such a replacement, the sandbox modifier 350 can ensure that the application 352 does not attempt to call an unauthorized function and/or “escape” the sandbox.
  • FIG. 4 is a flowchart of an example process 400 for testing software for signs of risk.
  • Each application signature represents a particular software application.
  • Each application signature includes operations each associated with a match score.
  • Each application signature includes a total score threshold. For example, a mobile computing device's security manager can download a pack of application signatures that each represent a particular software application found to be unwanted (e.g., malicious, containing unwanted features or security flaws).
  • operations performed by a software application instance executed by a computing device are monitored. For example, as the mobile computing device's operating system launches and executes applications, the operating system monitors operations performed by the software applications.
  • a particular operation performed by the software application instance matches an operation included in a particular application signature.
  • the operating system may identify a Boolean expression in a signature that, for a particular operation of a software application, is found to be true.
  • a match score associated with the particular operation is added to a total score associated with the software application instance.
  • the operating system may access a stored total score from a user's account in a cloud serve and add to the total score the match score.
  • the operating system may then report the updated match score to the cloud service.
  • the mobile device's operating system may report the match score, and the cloud service may compute the total score.
  • the software application instance in response to adding the match score to the total score, it is determined that the total score for the software application instance is greater than or equal to the total score threshold for the particular application signature.
  • the software application instance is classified as the particular software application represented by the particular application signature. For example, the mobile computing device may delete the software application, and the cloud service may generate an anonymized and/or aggregate report for a security researcher about the prevalence and behavior of the unwanted software application.
  • FIG. 5 is a flowchart of an example process 500 for identifying malicious application instances.
  • application signatures that identify operations to be monitored for, as well as operation sequences that specify an ordered list of operations. If tested software is found to match the operations of a signature, the weight value of those operations are added to the score for that signature. If those operations are also found to be performed in the order specified by an operation sequence, the weight of the operation sequence will also be added to the weight value for that signature.
  • This example process will use the example signature shown above.
  • Each application signature represents a particular software application.
  • Each application signature includes operations each associated with a match score, along with one or more operation sequence associated with a sequence weight.
  • Each application signature includes a total score threshold. For example, a mobile computing device's security manager can download a pack of application signatures that each represent a particular software application found to be unwanted (e.g., malicious, containing unwanted features or security flaws).
  • operations performed by a software application instance executed by a computing device are monitored. For example, as the mobile computing device's operating system launches and executes applications, the operating system monitors operations performed by the software applications. In this example, the operating system launches an application that attempts to modify a system library. This activity can be identified as matching the “libraries” event in the signature shown above, for a match score of 1.
  • operation sequences are matched. At this time, the only operations matched is the “libraries” event, which, on its own, does not match any of the operation sequences.
  • the match score is calculated. Currently, the match score is 1, and control returns to element 504 .
  • operations performed by a software application instance executed by a computing device are monitored.
  • the activity of the application is further monitored, and actions taken by the software to change the registry are identified as “registryKeys,” for a match score of 1.
  • the total score of 5 is found (e.g. 1+1+3) and compared to the “matchTotalScore” for the signature, which is a value of 3. As the total score of 5 is greater than or equal to 3, the software is identifies as matching this signature.
  • FIG. 6 is a schematic diagram that shows an example of a computing system 600 .
  • the computing system 600 can be used for some or all of the operations described previously, according to some implementations.
  • the computing system 600 includes a processor 610 , a memory 620 , a storage device 630 , and an input/output device 640 .
  • Each of the processor 610 , the memory 620 , the storage device 630 , and the input/output device 640 are interconnected using a system bus 650 .
  • the processor 610 is capable of processing instructions for execution within the computing system 600 .
  • the processor 610 is a single-threaded processor.
  • the processor 610 is a multi-threaded processor.
  • the processor 610 is capable of processing instructions stored in the memory 620 or on the storage device 630 to display graphical information for a user interface on the input/output device 640 .
  • the memory 620 stores information within the computing system 600 .
  • the memory 620 is a computer-readable medium.
  • the memory 620 is a volatile memory unit.
  • the memory 620 is a non-volatile memory unit.
  • the storage device 630 is capable of providing mass storage for the computing system 600 .
  • the storage device 630 is a computer-readable medium.
  • the storage device 630 may be a floppy disk device, a hard disk device, an optical disk device, or a tape device.
  • the input/output device 640 provides input/output operations for the computing system 600 .
  • the input/output device 640 includes a keyboard and/or pointing device.
  • the input/output device 640 includes a display unit for displaying graphical user interfaces.
  • the apparatus can be implemented in a computer program product tangibly embodied in an information carrier, e.g., in a machine-readable storage device, for execution by a programmable processor; and method steps can be performed by a programmable processor executing a program of instructions to perform functions of the described implementations by operating on input data and generating output.
  • the described features can be implemented advantageously in one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from, and to transmit data and instructions to, a data storage system, at least one input device, and at least one output device.
  • a computer program is a set of instructions that can be used, directly or indirectly, in a computer to perform a certain activity or bring about a certain result.
  • a computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.
  • Suitable processors for the execution of a program of instructions include, by way of example, both general and special purpose microprocessors, and the sole processor or one of multiple processors of any kind of computer.
  • a processor will receive instructions and data from a read-only memory or a random access memory or both.
  • the essential elements of a computer are a processor for executing instructions and one or more memories for storing instructions and data.
  • a computer will also include, or be operatively coupled to communicate with, one or more mass storage devices for storing data files; such devices include magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and optical disks.
  • Storage devices suitable for tangibly embodying computer program instructions and data include all forms of non-volatile memory, including by way of example semiconductor memory devices, such as EPROM (erasable programmable read-only memory), EEPROM (electrically erasable programmable read-only memory), and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM (compact disc read-only memory) and DVD-ROM (digital versatile disc read-only memory) disks.
  • semiconductor memory devices such as EPROM (erasable programmable read-only memory), EEPROM (electrically erasable programmable read-only memory), and flash memory devices
  • magnetic disks such as internal hard disks and removable disks
  • magneto-optical disks magneto-optical disks
  • CD-ROM compact disc read-only memory
  • DVD-ROM digital versatile disc read-only memory
  • a computer having a display device such as a CRT (cathode ray tube) or LCD (liquid crystal display) monitor for displaying information to the user and a keyboard and a pointing device such as a mouse or a trackball by which the user can provide input to the computer.
  • a display device such as a CRT (cathode ray tube) or LCD (liquid crystal display) monitor for displaying information to the user and a keyboard and a pointing device such as a mouse or a trackball by which the user can provide input to the computer.
  • Some features can be implemented in a computer system that includes a back-end component, such as a data server, or that includes a middleware component, such as an application server or an Internet server, or that includes a front-end component, such as a client computer having a graphical user interface or an Internet browser, or any combination of them.
  • the components of the system can be connected by any form or medium of digital data communication such as a communication network. Examples of communication networks include, e.g., a LAN (local area network), a WAN (wide area network), and the computers and networks forming the Internet.
  • the computer system can include clients and servers.
  • a client and server are generally remote from each other and typically interact through a network, such as the described one.
  • the relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

Abstract

Operations performed by a software application instance executed by a computing device are monitored. A determination is made that a particular operation performed matches an application signature representing a particular software application. In response, a match score is added to a total score for the software application. In response to determining that the total score is greater than or equal to a threshold, the software is classified.

Description

The present document relates to computer security.
BACKGROUND
Malicious software includes software programs that can or does perform actions that can harm or work against the interest of a user or computer system owner. Examples of such software include “adware” programs that monitor user behavior and present ads to the user, “spyware” programs that monitor user behavior, and computer viruses that may perform various malicious actions, including deleting files, and taking control of the user's computer to perform unauthorized operations.
All software applications, whether malicious or not, perform various operations during execution, such as, for example, accessing the file system, opening network ports, changing values stored in memory, and other operations.
SUMMARY
A method is performed by data processing apparatus. The method includes identifying application signatures each representing one or more software applications, each application signature including a total score threshold and one or more operation sequences each including a plurality of sequence operations, wherein each sequence listing is associated with a sequence score. The method further includes monitoring operations performed by a software application instance executed by a computing device. The method further includes determining that a first operation performed by the software application instance matches a first sequence operation included in a particular sequence listing for a particular application signature. The method further includes after determining that the first operation performed by the software application instance matches the first sequence operation, determining that a second operation performed by the software application instance matches a second sequence operation included in the particular sequence listing. The method further includes in response to determining that the second operation matches the second sequence operation, determining that each of the plurality of sequence operations for the particular sequence listing has been observed for the software application instance. The method further includes in response to determining that each of the plurality of sequence operations for the particular sequence listing has been observed, adding the sequence score to a total score for the software application instance. The method further includes in response to adding the sequence score to the total score, determining that the total score for the software application instance is greater than or equal to the total score threshold for the particular application signature. The method further includes in response to determining that the total score is greater than or equal to the total score threshold, classifying the software application instance as the software application represented by the particular application signature.
Implementations can include any, all, or none of the following features. Each application signature includes operations each associated with a match score. The method further comprises determining that the first particular operation performed by the software application instance matches an operation included in the particular application signature; and in response to determining that the first particular operation matches the operation included in the particular application signature, adding a match score associated with the particular operation to the total score associated with the software application instance. The sequence listing includes a particular order for the plurality of sequence operations, the first sequence operation being in a first position in the particular order, and the second sequence operation being in a final position in the particular order. Monitoring operations performed by a software application instance executed by a computing device comprises performing static analysis of one or more attributes of the software application instance. Performing static analysis of one or more attributes of the software application instance comprises determining if the one or more attributes match a preconfigured value in an application signature. The one or more attributes includes at least one of the group consisting of a Secure Hash Algorithm (SHA) value, an MD5 value, and a program name. The method further comprising performing, responsive to classifying the software application instance as the software application represented by the particular application signature, a configured action associated with the particular application signature. The configured action is selected from a plurality of actions based on a determination of a type of the computing device. The determined type is a network security device; and the configured action comprises terminating network traffic with a server that served the particular software application. The determined type is a client device that resides on a network; and the configured action comprises powering down the client device. The configured action comprises presenting, responsive to classifying the software application instance as the particular software application represented by the particular application signature, a report identifying i) the particular software application and ii) the particular application signature. The report further comprises a human-readable description of the particular application signature. The method further comprising generating the report from a template document that includes at least an application-related fillable field and a signature-related fillable field using data associated with the particular application signature. The software application instance executed by a computing device is executed on a client device. The software application instance executed by a computing device is executed in a sandbox environment. Each application signature represents a particular class of software application include the one or more software applications. The method further comprising: monitoring operations performed by a second software application instance executed by the computing device; determining that a particular operation performed by the second software application instance matches an operation included in the particular application signature; in response to determining that the particular operation matches the operation included in the particular application signature, adding a match score associated with the particular operation to a total score associated with the second software application instance; in response to adding the match score to the total score, determining that the total score for the software application instance is less than the total score threshold for the particular application signature; and in response to determining that the total score is greater than or equal to the total score threshold, allowing the second software application instance to continue execution without classifying it as the particular software application.
System and computer storage media encoded with computer program instructions are providing for performing similar operations.
DESCRIPTION OF DRAWINGS
FIGS. 1A, 1B, and 1C are block diagrams of example computer systems in which the present techniques for identifying malicious application instances may be implemented.
FIG. 2 is a swim-lane diagram of an example process for identifying malicious application instances.
FIGS. 3A and 3B are block diagrams of example computing sandbox techniques.
FIG. 4 is a flowchart of an example process for identifying malicious application instances.
FIG. 5 is a flowchart of an example process for identifying malicious application instances.
FIG. 6 is a schematic diagram that shows an example of a computing device and a mobile computing device.
Like reference symbols in the various drawings indicate like elements.
DETAILED DESCRIPTION
Application instances (e.g., software programs, data files) executing on a computer system may include malicious instructions, such as viruses, macros, scripts, or other instructions embedded in the object that perform malicious operations without the user's knowledge. Security programs such as anti-virus software generally scan a computer for known malicious application instances (such as by filename or based on a file signature of a virus or other malicious program), or monitor activity on the computer to detect such objects. Some malicious programs may include functionality to evade such security programs, such as by changing their own instructions or data footprint so as not to be recognized by a scan (a technique known as polymorphism), or by attacking the security software itself. Such security software may therefore be ineffective in some cases.
Accordingly, the present application describes techniques for identifying software applications as possibly malicious by detecting objects that perform operations matching an ordered list of operations. A framework is described in which signatures can be generated to represent software applications based on the operations they perform. The signatures may include ordered lists of operations known or suspected to be performed by the represented software application. Executing software application instances may then be monitored to identify operations performed by the instances that match operations in the application signatures. If a software application instance requests a particular sequence of operations included in a particular application signature, a match score associated with the particular operations may be added to a total score for the software application instance. In some cases, the total score represents a likelihood that the software application instance is an instance of the software application represented by the application signature. The particular application signature may also include a total score threshold indicating. If the total score associated with a software application instance is greater than or equal to the total score threshold for an application signature, the software application may be classified as an instance of the software application represented by the application signature. Upon classification, configured actions associated with the application signature may be performed, such as, for example, terminating the software application instance, deleting the software application from which the instance originated, quarantining the software application instance, alerting an administrator, updating the application signature based on information collected about the software application instance, or other actions. Some or all of these signatures may be used in different computer devices, providing a networked client device with a layered protection. For example, a network security device may identify a software application entering the network. Before passing the software application to the client device, the network security device may test the software application in a sandbox environment. If this software application does not get marked as risky by the network security device, the software application can be routed to the client device. At the client device, the execution of the software application can be monitored using some or all of the same signatures that were used in the sandbox.
In some cases, the application signatures may be used to identify software applications other than malicious ones. For example, an instance of a word processing program might be identified as that program based on the instance writing to a particular directory in the file system, based on registry keys it accesses during execution, display operations it requests during execution, or other operations.
The techniques described herein may provide the following advantages. By identifying application instances based on requested operations, the present techniques may be less affected by standard evasion techniques, such as polymorphism, used by viruses and other malicious programs, as the present techniques do not rely solely on detecting a program signature or other attribute of the malicious program. Generally, it is more difficult for a program to disguise its behavior than to disguise its structure, because altering the application behavior too greatly may prevent the application from achieving the objective it was originally designed to achieve. Further, by testing a software application with the same tests in different environments, a redundant protection scheme can provide computer devices with protection from context-dependent threats. Administrators can reuse signatures created for a virtual environment on live network environments without having to re-create a different set of signatures, saving time and making the signatures more effective as they may have already been tested in a virtual environment. Reports of malicious software applications can be generated to include information about what kind of signatures a software application matches and why a particular total score was calculated, giving network administrators or other users information needed to properly handle the risky application. By using files in a storage location to define signatures, the set of signatures used by my controlled by an administrated that can add, remove, and/or modify signatures as needed in a particular application. The administrator may also configure signatures to manage a particular threat. For example, a network being attacked by a custom advanced persistent threat can have signatures custom-created by the network administrator to defend against that advanced persistent threat. Also, the network administrator can create these rules without the inclusion of a third party (e.g., a security researcher or device vendor), thus providing the network administrator with the potential for a faster reaction time and the ability to properly manage disclosure of the attack. The signatures can include environment-specific tests and/or actions that are only applied in the applicable environment. For example, a signature may specify that a machine should power down when malware designed to encrypt the user's files is found.
FIGS. 1A and 1B are block diagrams of example environments in which the present techniques for identifying malicious application instances may be implemented. The computer network 100 includes a network gateway 102 that includes a sandbox environment for running unknown software. Also shown in the network 100 is a client device 106, which represents any appropriate computing device capable of browsing resources outside of the network 100. While not shown for clarity's sake, the network 100 can include other elements including, but not limited to, wireless and/or wired access points, file and/or application servers, routers, and network cables, as well as additional client devices 106 and/or network gateways 102.
The network 100 can be configured to route some or all of the messages addressed outside the network 100 to the network gateway 102. The network gateway 102 can inspect the messages and, optionally, modify or drop some messages. For example, the network gateway 102 may be configured to prevent traffic from a particular class of application (e.g., chat, files sharing). The network gateway 102 may also be configured to intercept messages intended for a recipient outside of the network 100 and reply directly.
Additionally, the network 100 can be configured to route some or all of the messages addressed into the network 100 through the network gateway 102. The network gateway 102 can inspect the messages and, optionally, modify or drop some messages. For example, the network gateway 102 may be configured to prevent traffic from a particular class of application (e.g., chat, files sharing). The network gateway 102 may also be configured to intercept messages intended for a recipient inside of the network 100 and reply directly.
The network gateway 102 may intercept some traffic addressed to recipients inside the network 100, for example to enforce security or other network policies. For example, one or more messages that contain application instances (e.g., executable binary instructions, interpretable scripts, or the like) that are addressed to a recipient in the network 100 can be received by the network gateway 102. Instead of routing the one or more messages, the network gateway 102 may instead test the application instance to determine if it is likely to be malicious. If it is determined not likely to be malicious, the network gateway 102 may then route the message or message on their way to the addressed recipient. If the application instance is determined to be malicious, the network gateway 102 may take an appropriate action such as deleting the software, serving a webpage to the intended recipient indicating that the application instance was found to be malicious, or holding the software in quarantine of further testing or analysis. Examples of determining malicious application instances are described below.
In one example, the client device 106 generates a request message 108 addressed to a resource hosted on a server 104. This request may be, for example, a hypertext transfer protocol (HTTP) GET message that includes the universal resource locator (URL) of the server 104 or a resource hosted on the server 104. The network gateway 102 may, possibly after examining the request 108 for any applicable security or network policies, route the request 108 to the server 104.
The server 104 can receive the request 108 and determine that the server 104 should reply by serving the requested resource. To do so, the server 104 can create a response 110 that includes the requested resource. The server 104 can send this response 110 to the client device 106. To reach the client device 106, the response 110 can be routed through the network gateway 102. Instead of routing the response 110 to the client device 106, the network gateway 102 can intercept the response 110 to determine 114 if the response 110 complies with security or other network policies of the network 100.
For example, the network gateway 102 may include rules 103 that define a security policies of the network. One such policy may specify that particular application instances should be tested in a sandbox. In general, a sandbox is a controlled execution environment where, for example, an unknown application instance can be run without allowing the application instance to access critical components of a computing device.
Instead of routing the reply 110 to the client device 106, the network gateway 102 can initiate a sandbox 112 and run the application instance attached to the reply 110. The sandbox 112 can allow the application instance to run, install, or open it using an associated application, such as using a word processing program to open a text document. The sandbox 112 can apply one or more tests to the application instance to determine if the application instance contains malicious functionality or is likely to contain malicious functionality. For example, the sandbox 112 may execute the application instance for a period of time, and compare the behavior and features of the running instance against a suite of signatures designed to identify potentially malicious or unwanted software applications. Examples of these signatures is described below.
If the application instance is determined to be malicious, the network gateway 102 may take an appropriate action. These actions may be specified by the rules 103. For example, the network gateway 102 may drop any communications with the server 104, may quarantine the received application instance, and/or may subject the application instance to additional testing. This additional testing may, for example, take longer than the initial tests used to determine the application instance is malicious. In some cases, the additional testing may be more accurate, but at the cost of processing time.
In these cases, a webpage or other message may be served to the client device 106 informing the client device 106 that the reply 110 has been blocked. If the application instance is found to be low-risk or found not to contain malicious behavior, the reply 110 may be sent to the client device.
Referring to FIG. 1B, the network 130 differs from the network 100 of FIG. 1A at least in that the client device 106 hosts the sandbox 112 instead of the network gateway 102 hosting the sandbox 112. In other examples, both the network gateway 102 and the client device 106 may host their own sandboxes 112.
Hosting the sandbox at the client devices 106 instead of the network gateway 102 may have a number of implications for the computers systems. For example, by hosting the sandbox 112 at the only network gateway 102, or all network gateways if a network has more than one, a network administrator can ensure that all traffic into the network can be subject to sandbox-based analysis. By hosting sandboxes at each client device 106, different sandboxes with different rules may be used by client devices of different types. For example, a server hosting customer payment data may have a more rigorous testing scheme than user workstation computers. In a case where the network administrator does not own or administer client device 106, the network administrator may only be able to configure a sandbox 112 at the network gateway 102 and the client device 106 owners may only be able to configure a sandbox 112 at their own client devices 106.
While the client device 106 is shown hosting the sandbox 112 to run the resource, the use of a sandbox is not required. For example, the client device 106 may host one or more sandboxes and run the resource natively, or may not host any sandboxes.
FIG. 1C shows an example of a computer 150 that monitors application instances. The computer 150 includes an operating system 152 that hosts an application monitor 154, an executable 156, a document viewer 158 displaying a file 160 and a virtual machine 162 running a script 164. While not shown for clarity's sake, the computer 150 can include other elements including, but not limited to, input and output components, networking components, and other hardware and software.
The computer 150 can include any type of computer system that can execute an application instance. Examples include, but are not limited to, desktop or laptop computers, server systems, mobile computing devices, or embedded computing devices (e.g., controllers in ‘smart’ appliances, automotive computing systems). The computer 150 includes and operating system 152, or other similar system, to host running application, provide those applications with an interface to the computer 150, to manage communications and storage, and for other purposes.
An application monitor 154 can run in the operating system, and/or may be a part of the operating system 152. The application monitor 154 may be configured to identify an execution of a application instance by the computer 150. The execution of a application instance can include, but is not limited to, the executable file 156 being executed, the file 160 being opened or used by the document viewer 158, and the script 164 running in the virtual machine 162.
In response to identifying the execution of the application instance, the application monitor 154 can monitor the activities of the executing application instance. For example, the application monitor 154 may monitor the system calls of the executable 156 to check for an indication of malicious behavior.
One type of malicious behavior includes an application performing sensitive actions before interacting with a user of the computer 150. For example, a normally functioning application will often draw a graphical user interface and present the interface to the user before accessing sensitive portions of the operating system 152. On the other hand, a malicious piece of adware may, instead of interacting with the user, install plug-ins to the user's web browser redirecting traffic to a network resource associated with the adware in order to monitor the user's web traffic.
If the application monitor 154 determines that the application instance has requested a sensitive action before interacting with a user of the computer 150, the application monitor can classify, or cause another element to classify, the running application instance as a malicious application instance. For example, the application monitor 154 may report to security software on the computer 150 (not shown) that the executable 156 has written data outside the executable 156's directory before interacting with the user. The security software may use this as one signal to determine if the executable 156 is to be classified as malicious. For example, if the executable 156 is on a whitelist of known-good application, the executable 156 may be allowed to run as normal. If, on the other hand, the executable 156 provides other signals of risk (e.g., newly loaded onto the operating system 152, containing encrypted containers that are decrypted at runtime, sporadically sending large amounts of data over the network) the security software may delete, isolate in a sandbox, or otherwise handle the executable 156 in a way that protects the computer 150.
In some cases, combinations of the systems described in FIGS. 1A-1C may be used. For example, the network gateway may test an incoming software application against a set of signatures, and then the client device 106 or 150 may test the incoming software again. Such a configuration may provide a computer device with defense in depth through redundant protection against malicious applications. For example, some if a sandbox test performed by a network security device tests a software application and determines that it is not a malicious application, the client system can still test the software application an additional time. This may be useful, for example, in cases where a software application displays different behavior in different environments.
In some cases, the software application to be tested may not be an incoming software application. For example, the client device 106 or 150 may be configured to monitor the behavior of some, any, or all application running natively or in managed environments (e.g. sandboxes). For example, component of the operating system or an installable security application may perform the testing described in this document on all running applications, applications lacking known signed certificates, or a sample (random or otherwise) of software application instances.
Consider a Trojan program (e.g., a software application including a malicious payload) that is designed to deploy a malicious payload only if it detects a particular operating system having a known vulnerability. If that vulnerability is not detected, the Trojan program creates a user interface window for a video game. A client on a network can attempt to download this Trojan program. Before routing the Trojan program to the client device, a network security device (e.g., a router, a firewall, or other network attached device) can test the Trojan program in a sandbox environment. If the sandbox environment does not emulate the vulnerable operating system, the Trojan Program may act like an innocuous video game. As such, the network security device may calculate a total score based on the behavior of an instance of the Trojan program that does not classify it as the Trojan program. The network security device may then route the Trojan program to the client device that requested it. Once installed there, the Trojan program may attempt to deploy its malicious payload. By monitoring the execution of an instance of the Trojan program, the client device may detect the behavior of the malicious payload upon deployment, classify the instance as the Trojan program, and take appropriate action. For example, the client application may terminate the Trojan program and alert a network administrator.
There are other types of application that may be configured to behave differently in different environments. For example, some malware is known to sleep in virtual environments and activate outside of virtual environments. A “spearfishing attack” may be configured to only deploy if a particular user or device configuration is found. An unwanted application plug-in (e.g., bundled into another program's installer application) may only install if the target application is found. Testing in both the virtual and non-virtual environments may be used to successfully identify any of these types of attacks, as well as other types of advanced persistent threats, advanced evasive threats, and advanced evasive malware.
In example where different devices monitor the execution of a software application, each device may use the same, or some of the same, signatures to test the software application. For example, a set of signatures may be developed to detect a particular unwanted toolbar application. These signatures may be used in dynamic tests such as monitoring the user preferences of a web browser and static testing such as examining the toolbar application to see if it contains a class known or believed to be common to unwanted toolbars. These signatures may be used by any kind of computing device (e.g., a network computing device, a client device, a device hosting a sandbox) monitoring the execution of a software application.
In addition or alternatively, some but not all of the devices may use different rules, even if those devices are all administered by the same organization. For example, a suite of sandbox-specific signatures crafted to catch behavior of applications attempting to escape a sandbox. Example behaviors include, but are not limited to return-oriented programming, writing to memory locations outside of a permitted range, and attempting to escalate execution privileges. Devices that run applications in a sandbox environment may be given these signature while, optionally, devices that don't run applications in a sandbox may not. Other suites of signatures like this can include, but are not limited to, operating system specific signatures, hardware specific signatures, or user specific signatures. In addition to feature-specific signatures, devices may also use universal suites of signatures that can be use universally (e.g. for every device under a particular administration, on a network, or otherwise logically grouped).
The signatures can have associated actions. For example a file defining a signature may identify, reference, or otherwise associate the signature with one or more action. These actions might include, for example, generating a report from a template to describe the type of software application identified, closing a network communication channel, deleting the software application, terminating the software application's running instance, or powering down the device executing the software application.
The action may be conditional based on the type of device running the test. For example, a particular or pair of signatures may specify that a network security device be configured to terminate a client's communication with a server, while a client device be configured to shut down. The signature may also include universal actions to be performed without regard to the device running the test. For example, a reporting action may be specified as universal such that any detection by any device results in report generation.
Reports when a signature is matched may be programmatically generated. In some cases, this generation may be automatic—that is, without specific user input to cause the report to be generated. One process for generating this report is to create a copy of a document template (e.g. of a webpage, of an email, of a text message) and to populate fields of that template with information about the signature, the environment, the application, etc. This report may be logged and/or transmitted, for example to a network administrator tasked with protecting a network and/or to a security researcher tasked with identifying trends in the computer security field.
The number of times that a software application is tested may dependent on the configuration of the network or networks to which a client device is connected. For example, a client device may reside on a network protected with a network security device that performs the testing described in this document. While on that network, the client device may be protected by two layers of security—one layer being the testing by the network security device and one layer being the testing performed by the client itself.
Later, that client device may leave the network and join another network (e.g., a user takes their laptop from their school to a coffee shop). This new network may not be configured to provide this testing. In this configuration, this same client is now protected by only a single layer—the testing performed by the client itself.
Once connected to the second network, the client may virtually join the first network using a Virtual Private Network (VPN) client. Some VPNs are configured such that general web browsing is routed through the virtual network before reaching the client. The client may or may not be protected by another layer of protection depending on if the VPN is configured to perform the testing described. This usage may be repeated for any sort of technologically appropriate overlay network.
Signatures may be available for user inspection, creation, an editing. For example, a suite of signatures may be a collection of files stored by a computing device (e.g., in the rules 103) or otherwise accessible to the computing device. These signature files may be in a standard or custom file format that a user may be able to view and/or edit in a human-readable form. One such form is a text file (e.g., an Extensible Markup Language (XML), JavaScript Object Notation (JSON), or other file) containing regular expressions (regexes) or other Boolean matching rules. As such, signatures may be created by a variety of users, including but not limited to, network administrators, the users of a single client device, security professionals and device vendors.
Testing using these signatures may include both static and dynamic testing. In general, static testing includes the testing of a static portion of a software application or testing of the application without the need to run the software application. Example of static testing include, but are not limited to, examination of a file, comparison of a hash of the software application (e.g., Secure Hash Algorithm (SHA), MD5), identification of a pseudorandom number in the software application (e.g., as a registry value), or the presence or absence of a particular software component (e.g., a cryptographic library and/or an opaque application instance).
In general, dynamic testing includes observations made while an instance of the software application is executing. Examples of dynamic testing include, but are not limited to, examination of system calls by the software application, documenting data written to memory, and monitoring network communications made by the software application. In some cases, dynamic testing can include identifying if the software application performs actions that match an ordered sequence of signatures. For example, a signature file may be configured to test if an application writes a value to the registry, accesses memory outside of a local directory, and then initiates a network query, in that order.
A test suite of signatures can be configured to include a list of categories, each represented for example by one text file. Each category may include, for example, configuration data and a list of signatures. The configuration data may include, for example, variable values set for a particular category. The list of signatures may be a list of regular expressions (regexes) or other Boolean matching rules. In general, a regex are a sequence of characters that forms a search pattern, mainly for use in pattern matching with strings, or string matching. For each such signature, a weight may be assigned that may indicate, for example, how dispositive a rule is. For example, if a rule is very likely to be dispositive to determining that a software application fits a particular profile, the weight may be higher than for a rule that is only slightly indicative that a software application fits a particular profile.
When a software application and/or software application instance is tested against a category of signatures, each matching signature can be assigned a mark and a summation of all marked signatures weights may be made. Then, the number of marks and/or the summarized weights may be compared to one or more threshold values to determine a risk metric for the software application. These threshold values may be defined, for example, in the configuration data of the category.
In addition to matching particular signatures, the score may then be augmented if the matches occur based on a particular ordered sequence. Each sequence identifies a particular order of operations that a tested piece of software may execute, with or without other operations in between. If the sequence is matched, a sequence weight can be applied to the summation of the signature marks in order to increase or decrease the weight. For example, it may be determined that software that accesses a registry, then modifies system libraries is likely malicious. In such a situation, a signature may exist to monitor for access of the registry and another for modifications to the library. If both of those actions are performed out of order, the weight for that application would be the sum of those two signatures. If, however, the actions are performed in the specified order, the weight can be modified with an additional weight associated with the order. Since it was determined that performance of those actions in order is more indicative of problematic software, software with those actions in order result in a greater final weight.
The ordered sequence may be set to a ‘strict ordering’ or not. For ‘strict ordering’ sequences, the ordered sequences must be performed in order, without other operations being performed in between elements of the sequence. For sequences that are not identified as strict, other operations may be performed in between the operations of the sequence and a match may still be found.
For example, a sequence identifies an OS system call followed by a network communication and an application instance calls the OS system call, writes data to memory, and then begins a network communication. If the sequence is set as strict, this would not be a match. If the sequence is not set to strict, this would be a match.
A single threshold may be used to classify an instance of a software application as either risky or not, of a particular class of software or not, etc. Multiple thresholds may be used to place the instance of a software application into a multi-band metric. For example, a software application instance is tested against a particular category, and the result is two marks and a nineteen weight.
If there is only a single threshold value of weight=20, this software application could be categorized as failing the test. If, in another configuration, threshold values of weight=15 and weight=20, the software application can be categorized as moderately risky, or moderately matching, etc. A number of marks may also be used as a threshold. For example, a category may be configured with thresholds of weight=15 and marks=3. In this example, the tested software application instance can also be categorized as moderately risky, or moderately matching, etc.
An example of a single category of signatures is shown below. This category is created in a single .JSON text file. As shown, the category of signatures includes configuration at the beginning of the file, followed by a list of signatures. Each of the signatures has an associated “sequenceOrder” value. For positive integer values of “sequenceOrder” the signatures must be matched in the order of the values. For “sequenceOrder” values of −1, a sequence could be matched in any order.
{
 “version”: 1,     //the overall signature protocol version, has
nothing to do with the signature version
 “namespace”: “examplespace”,    //source of the signature, 1 =
human-generated, 2 = auto-generated
 “sid”: 1,     //1-1,000,000 are reserved
 “name”: “cryptomalware”,
 “description”: “Behavioral signature for crypto malware.”,
 “revision”: 1.1,
 “classification”: “trojan-activity”,  //human readable classification
 “category”: “malware”,      //general category, spyware,
malware, exploit, etc.
 “priority”: 1,      //1-4 (1 being highest)
 “license”: “iboss, Inc.”,
 “author”: “example threat labs”,
 “osType”: “all”,     //what operating system is this relevant to? (all,
or list specific examples)
 “osVersion”: “all”,   //what version of the operating system is this
relevant to (all, or list specific examples),
 “osPlatform”: “all”,   //what os platform (32 bit, 64 bit, all)
 “actions”: [“log”,“block”], // from enum of [“alert”, “log”, “block”,
“pass” “powerdown”]//what to do when signature matches (alert, email,
text, powerdown) // powerdown is only available in live environments
 “reference”: “http://firesphere.iboss.com/ref?id=123”,
“matchTotalScore:”: 3,   //the total score that makes this signature a
100% match
 “enabled”: true,    // enables/disables the rule
 “signature”: {
  “files”: [
   {
    “signatureTag”: “eicar in program files”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “sizeMinBytes”:0,
    “sizeMaxBytes”:0,  //0 = no max
    “fileTypes”:[“any”, “binary”, “ascii”, “executable” ],
    “filePath”: “C:/ProgramFiles”,
    “searchRecursive”: true,
    “recursiveSearchDepth”: 0,  //0 = infinite, 1 = the path above,
2 = the path above + its direct folders
    “matchPattern”: “*eicar*”, //pcre regular expression
    “matchLowercase”: 0,    //convert the sample to lowercase
before applying match patterns
    “operationType”: [“any”, “downloaded”, “copied”, “opened”,
“moved”, “read”, “write”, “replaced”, “deleted”, “created” ],
     “sequenceOrder”: 1
   }
  ],
  “registryKeys”: [
   {
    “signatureTag”: “registry tampering”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “keyPath”: “HKEY_LOCAL_MACHINE/SOFTWARE”,
    “searchRecursive”: true,
    “recursiveSearchDepth”: 0,  //0 = infinite, 1 = the path above,
2 = the path above + its direct reg keys
    “matchPattern”: “crypto”, //pcre regular expression
    “matchLowercase”: 0,   //convert the sample to lowercase
before applying match patterns
    “operationType”: [“any”, “created”, “opened”, “renamed”, “read”,
“write”, “deleted” ],
     “sequenceOrder”: 2
   }
  ],
  “osHooks”: [
   {
    “signatureTag”: “system tampering”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “hookMatchPattern”: [“WH_MSGFILTER”],  //pcre regular
expression
    “hookMatchLowercase”: 0,     //convert the sample to
lowercase before applying match patterns
    “methodMatchPattern”: “SetWindowsHook”,  //pcre regular
expression
    “methodMatchLowercase”: 0,    //convert the sample to
lowercase before applying match patterns
    “operationSuccessful”: [“true”, “false”, “any”], //only match if
hook was successful, etc
     “sequenceOrder”: −1
   }
  ],
  “mutexes”: [
   {
    “signatureTag”: “mutex created”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “matchPattern”: “*lock*”,  //pcre regular expression
    “matchLowercase”: true,     //convert the sample to lower-
case before applying match patterns//
    “operationType”: [“any”, “created”, “opened” ],
    “operationSuccessful”: [“true”, “false”, “any”],  //only match if
hook was successful, etc
    “sequenceOrder”: 3
    }
  ],
  “libraries”: [
   {
    “signatureTag”: “dll present”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “matchPattern”: “*user32*”,  //pcre regular expression
    “matchLowercase”: true,     //convert the sample to lower-
case before applying match patterns//
    “operationType”: [“any”, “loaded”, “created”, “deleted”,
“modified” ],
    “operationSuccessful”: [“true”, “false”, “any”],  //only match if
hook was successful, etc
    “sequenceOrder”: −1
    }
  ],
  “services”: [
   {
    “signatureTag”: “service detected”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “matchPattern”: “*mpssvc*”,  //pcre regular expression
    “matchLowercase”: true,     //convert the sample to lower-
case before applying match patterns//
    “operationType”: [“any”, “deleted”, “opened”, “controlled”,
“created”, “started”, “service_manager” ],
   “operationSuccessful”: [“true”, “false”, “any”],  //only match if
hook was successful, etc
   “sequenceOrder”: 4
   }
  ],
  “processes”: [
   {
    “signatureTag”: “process signature”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “processIds”: [225,335], // would this ever be useful?
    “matchPattern”: “*lock*”,  //pcre regular expression
    “matchLowercase”: true,     //convert the sample to lower-
case before applying match patterns//
    “operationType”: [“any”, “present”, “injected”, “created”,
“terminated”, “shellcommand”],
    “parentMatchPattern”: “*lock*”,  //parent process name
    “parentMatchLowercase”: true,
     “sequenceOrder”: −1
   }
  ],
  “staticSamples”: [
  {
    “signatureTag”: “the file sample itself”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “matchType”: “magic_literal”,  //magic_literal, trid, file_content,
memory_map
    “matchPattern”: “*eicar*”,  //pcre for magic_literal/trid. hex for
file_content/memory_map
    “matchLowercase”: true,
     “sequenceOrder”: −1,
    }
  ],
  “networkActivity”: [
   {
    “signatureTag”:“dns network match”,
    “score”: 1,  //adds to the match_total_score
    “protocol”: “dns”,      //dns, tcp, udp, https, ip
    “matchType”: “query”,     //query, response (may be
extended to include things like ttl, etc.
    “matchPattern”: “*google.com*”,  //pcre regular expression
    “matchLowercase”: true,  //convert the sample to lowercase
before applying match patterns
     “sequenceOrder”: −1
    },
   {
    “signatureTag”:“ip network match”,
    “score”: 1,  //adds to the match_total_score
    “protocol”: “ip”,      //dns, tcp, udp, http, ip, any
    “matchType”: “source_ip”,   //source_ip, destination_ip
    “matchPattern”: “74.125.*”,   //pcre regular expression
    “sequenceOrder”: −1
    },
   {
    “signatureTag”:“tcp network match”,
    “score”: 1,  //adds to the match_total_score
    “protocol”: “tcp”,     //dns, tcp, udp, http, ip, any
    “matchType”: “source port”,   //source_port, destination_port
    “ports”: [“80”, “25-30”]   //single ports and port ranges
    “sequenceOrder”: −1
    },
   {
    “signatureTag”:“udp network match”,
    “score”: 1,  //adds to the match_total_score
    “protocol”: “udp”,    //dns, tcp, udp, http, ip, any
    “matchType”: “source_port”,  //source_port, destination_port
    “ports”: [“80”, “25-30”]  //single ports and port ranges
     “sequenceOrder”: −1
    },
   {
    “signatureTag”:“http network match”,
    “score”: 1,  //adds to the match_total_score
    “protocol”: “http”,    //dns, tcp, udp, http, ip, any
    “matchType”: “url”,   //url, header_option
    “matchPattern”: “google.com/fetch.php?*”,   //pcre regular
expression
    “matchLowercase”: true  //convert the sample to lowercase
before applying match patterns
    “sequenceOrder”: −1
    },
   {
    “signatureTag”:“https network match”,
    “score”: 1, //adds to the match_total_score
    “protocol”: “https”,      //dns, tcp, udp, http, ip, any
    “matchType”: “cert_domain”,     //cert_domain
    “matchPattern”: “www.google.com”,  //pcre regular expression
    “matchLowercase”: true   //convert the sample to lowercase
before applying match patterns
    “sequenceOrder”: −1
    }
   ]
  }
}
Another example of a single category of signatures is shown below. This category is created in a single .JSON text file. As shown, the category of signatures includes configuration at the beginning of the file, followed by a list of signatures. Each signature specifies a Boolean test an associated tags used for the test, in reporting the results of the signature, etc. Although this particular example is shown, other formats are possible.
{
 “version”: 1,    //the overall signature protocol version, has
nothing to do with the signature version
 “namespace”: “examplespace”,     //source of the signature, 1 =
human-generated, 2 = auto-generated
 “sid”: 1,     //1-1,000,000 are reserved
 “name”: “cryptomalware”,
 “description”: “Behavioral signature for crypto malware.”,
 “revision”: 1.1,
 “classification”: “trojan-activity”,  //human readable classification
 “category”: “malware”,      //general category, spyware,
malware, exploit, etc.
 “priority”: 1,       //1-4 (1 being highest)
 “license”: “iboss, Inc.”,
 “author”: “example threat labs”,
 “osType”: “all”,     //what operating system is this relevant
to? (all, or list specific examples)
 “osVersion”: “all”,    //what version of the operating system is this
relevant to (all, or list specific examples),
 “osPlatform”: “all”,   //what os platform (32 bit, 64 bit, all)
 “actions”: [“log”,“block”], // from enum of [“alert”, “log”, “block”,
“pass” “powerdown”]//what to do when signature matches (alert, email,
text, powerdown) // powerdown is only available in live environments
 “reference”: “http://firesphere.iboss.com/ref?id=123”,
 “matchTotalScore:”: 3,   //the total score that makes this signature a
100% match
 “enabled”: true,     // enables/disables the rule
 “signature”: {
  “files”: [
   {
    “signatureTag”: “eicar in program files”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “sizeMinBytes”:0,
    “sizeMaxBytes”:0,  //0 = no max
    “fileTypes”:[“any”, “binary”, “ascii”, “executable” ],
    “filePath”: “C:/ProgramFiles”,
    “searchRecursive”: true,
    “recursiveSearchDepth”: 0,  //0 = infinite, 1 = the path above,
2 = the path above + its direct folders
    “matchPattern”: “*eicar*”, //pcre regular expression
    “matchLowercase”: 0,   //convert the sample to lowercase
before applying match patterns
    “operationType”: [“any”, “downloaded”, “copied”, “opened”,
“moved”, “read”, “write”, “replaced”, “deleted”, “created” ]
   }
  ],
  “registryKeys”: [
   {
    “signatureTag”: “registry tampering”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “keyPath”: “HKEY_LOCAL_MACHINE/SOFTWARE”,
    “searchRecursive”: true,
    “recursiveSearchDepth”: 0,  //0 = infinite, 1 = the path above,
2 = the path above + its direct reg keys
    “matchPattern”: “crypto”,  //pcre regular expression
    “matchLowercase”: 0,    //convert the sample to lowercase
before applying match patterns
    “operationType”: [“any”, “created”, “opened”, “renamed”,
“read”, “write”, “deleted” ]
   }
  ],
  “osHooks”: [
   {
    “signatureTag”: “system tampering”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “hookMatchPattern”: [“WH_MSGFILTER”],  //pcre regular
expression
    “hookMatchLowercase”: 0,     //convert the sample to
lowercase before applying match patterns
    “methodMatchPattern”: “SetWindowsHook”,  //pcre regular
expression
    “methodMatchLowercase”: 0,    //convert the sample to
lowercase before applying match patterns
    “operationSuccessful”: [“true”, “false”, “any”]  //only match if
hook was successful, etc
   }
  ],
  “mutexes”: [
   {
    “signatureTag”: “mutex created”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “matchPattern”: “*lock*”,  //pcre regular expression
    “matchLowercase”: true,     //convert the sample to
lowercase before applying match patterns//
    “operationType”: [“any”, “created”, “opened” ],
    “operationSuccessful”: [“true”, “false”, “any”]  //only match if
hook was successful, etc
   }
  ],
  “libraries”: [
   {
    “signatureTag”: “dll present”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “matchPattern”: “*user32*”,  //pcre regular expression
    “matchLowercase”: true,     //convert the sample to
lowercase before applying match patterns//
    “operationType”: [“any”, “loaded”, “created”, “deleted”,
“modified” ],
    “operationSuccessful”: [“true”, “false”, “any”]  //only match if
hook was successful, etc
   }
  ],
  “services”: [
   {
    “signatureTag”: “service detected”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “matchPattern”: “*mpssvc*”,  //pcre regular expression
    “matchLowercase”: true,     //convert the sample to
lowercase before applying match patterns//
    “operationType”: [“any”, “deleted”, “opened”, “controlled”,
“created”, “started”, “service manager” ],
    “operationSuccessful”: [“true”, “false”, “any”]  //only match if
hook was successful, etc
   }
  ],
  “processes”: [
   {
    “signatureTag”: “process signature”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “processIds”: [225,335], // would this ever be useful?
    “matchPattern”: “*lock*”,  //pcre regular expression
    “matchLowercase”: true,     //convert the sample to
lowercase before applying match patterns//
    “operationType”: [“any”, “present”, “injected”, “created”,
“terminated”, “shellcommand”],
    “parentMatchPattern”: “*lock*”,  //parent process name
    “parentMatchLowercase”: true
   }
  ],
  “staticSamples”: [
   {
    “signatureTag”: “the file sample itself”,  //arbitrary name
    “score”: 1,  //adds to the match_total_score
    “matchType”: “magic_literal”,  //magic_literal, trid, file_content,
memory_map
    “matchPattern”: “*eicar*”,   //pcre for magic_literal/trid. hex
for file_content/memory_map
    “matchLowercase”: true
   }
  ],
  “networkActivity”: [
   {
    “signatureTag”:“dns network match”,
    “score”: 1,  //adds to the match_total_score
    “protocol”: “dns”,      //dns, tcp, udp, https, ip
    “matchType”: “query”,     //query, response (may be
extended to include things like ttl, etc.
    “matchPattern”: “*google.com*”,   //pcre regular expression
    “matchLowercase”: true   //convert the sample to lowercase
before applying match patterns
   },
   {
    “signatureTag”:“ip network match”,
    “score”: 1,  //adds to the match_total_score
    “protocol”: “ip”,      //dns, tcp, udp, http, ip, any
    “matchType”: “source_ip”,   //source_ip, destination_ip
    “matchPattern”: “74.125.*”   //pcre regular expression
   },
   {
    “signatureTag”:“tcp network match”,
    “score”: 1,  //adds to the match_total_score
    “protocol”: “tcp”,     //dns, tcp, udp, http, ip, any
    “matchType”: “source_port”,   //source_port, destination_port
    “ports”: [“80”, “25-30”]   //single ports and port ranges
   },
   {
    “signatureTag”:“udp network match”,
    “score”: 1,  //adds to the match_total_score
    “protocol”: “udp”,     //dns, tcp, udp, http, ip, any
    “matchType”: “source_port”,   //source_port, destination_port
    “ports”: [“80”, “25-30”]   //single ports and port ranges
   },
   {
    “signatureTag”:“http network match”,
    “score”: 1,  //adds to the match_total_score
    “protocol”: “http”,     //dns, tcp, udp, http, ip, any
    “matchType”: “url”,    //url, header_option
    “matchPattern”: “google.com/fetch.php?*”,  //pcre regular
expression
    “matchLowercase”: true  //convert the sample to lowercase
before applying match patterns
   },
   {
    “signatureTag”:“https network match”,
    “score”: 1,  //adds to the match_total_score
    “protocol”: “https”,     //dns, tcp, udp, http, ip, any
    “matchType”: “cert_domain”,     //cert_domain
    “matchPattern”: “www.google.com”,  //pcre regular expression
    “matchLowercase”: true  //convert the sample to lowercase
before applying match patterns
   }
  ]
  “sequence”: [
     {
      “signatureTag”: “Targeting system files”,  //change to DLLs
  followed by a change to the registry
    “score”: 3,  //adds to the match_total_score
    “sequence list”:   “dll present”, “registry tampering”
    “strictOrder”:1
    }
    {
    “signatureTag”:  “Exfiltrating data”, //identifying system infor-
mation and reporting to command and control
    “score”: 7 //adds to the match_total_score
    “sequence list”:   “service detected”, “ip network match”
    “strictOrder”:0
   }
  ]
 }
}
FIG. 2 is a swim-lane diagram of an example process 200 for testing software for signs of risk. For clarity, the process 200 is being described with reference to the elements shown in FIGS. 1A and 1C. However, other components, including but not limited to those shown in FIG. 1B, may be used to perform the process 200 or similar processes.
The computer 150 requests 202 a software application. The server 104 serves 204 the software application. For example, a user on the computer 150 sends a request to the server 104 (e.g., a hypertext transfer protocol (HTTP) GET request, a file transfer protocol (FTP) RETR command) to serve a software application. In response, the server 104 can marshal a copy of the software application and send the software application to the computer 150 in an appropriate reply message.
The network gateway 102 intercepts 206 the software application. For example, the network gateway 102 can monitor traffic addressed to and from the computer 150 and intercept the traffic containing the software application.
The network gateway 102 runs 208 an instance of the software application in the sandbox 112 and monitors 210 the execution of the software application in the sandbox 112. For example, instead of routing the intercepted traffic to the computer 150, as it is addressed, the network gateway 102 can run a copy of the intercepted software application in a security sandbox on the same or different hardware. While the instance of the software application runs, the network gateway 102, or another appropriate device, can monitor the instance of the software application. This monitoring can include comparing the software application instance to one or more signatures that define tests to determine if the software application fits a profile of software that should be excluded from computers on the network (e.g., matching the software to a list of signatures and a group of ordered lists of signatures).
If the software application fails the test 212, the network gateway 102 performs a configured action 214. For example, if the software application instance matches one or more signatures, or if the number or weight of matching signatures is greater than one or more threshold values, the network gateway 102 can perform one or more configured actions. These actions can include actions specified by the signatures or other files, or may be performed if any software application instance fails a test. These actions include, but are not limited to creating an alert, generating a log entry, blocking the software application, and/or passing the software application to the computer 150.
In the case of passing the software application, the particular signature tripped may be configured to identify software applications that are desired. For example, consider an example of a corporate network that deploys a browser toolbar to the client machines on the network. This corporation's toolbar may be the only desired toolbar and all other toolbars should be excluded. A set of signatures that is configured to identify any toolbar would match both undesired and the desired toolbar.
In such a case, the corporate network's administrator may make a set of signatures with negative weight targeting the corporate toolbar only (e.g., by matching a publisher certificate signed by the corporation). In this case, the signatures that identify any toolbar may generate a positive weight offset by the negative weight of the targeted corporate-toolbar signatures.
In another case, the corporate network's administrator may make a category of signatures to identify the corporate toolbar, and, if the category finds a match, pass the software application to its intended recipient instead of blocking it or generating an alert.
If the software application passes the test (at 212), the network gateway 102 returns the software application to the computer 150 at 216. For example, if the software application's instance does not exhibit any features or behavior that identify the software as unwanted, the network gateway 102 can pass the software application to the computer 150
At 218, the computer 150 executes the software application and performs a test 220 on the executing instance of the software application. For example, the computer can run, interpret, load, or otherwise execute the software application. This execution may be monitored by the computer 150, using the same, similar, or different rules than the network gateway 102 used.
If the software application fails the test (at 222), the computer 150 performs the configured action 224. For example, the computer 150 may take the same, similar, or different action than those of the network gateway 102, depending on the configuration.
FIGS. 3A and 3B are block diagrams of example computing sandbox techniques.
In FIG. 3A, a computer system 300 hosts a sandbox for running applications. The computer system 300 includes hardware 302, an operating system 304 running on the hardware 302, and a sandbox 306 hosted by the operating system.
The hardware 302 includes the collection of physical elements of the computer system 300. The hardware 302 shown includes a processor 308, memory 310, and I/O devices 312, though other configurations are possible. The processor 308 is one or more computing processors capable of carrying out computing instructions. The memory 310 includes long term storage (e.g., hard disk) and system memory (e.g., Random Access Memory (RAM) components). The I/O devices 312 include hardware for input and output, such as for communicating with users and other computer systems. Example I/O devices include, but are not limited to, keyboards, pointer devices, speakers, and network connections.
The operating system 304 may run on the computer hardware 302. In general, the operating system is software that manages computer hardware and software resources and provides common services for computer programs. The operating system includes system functions 314. These system functions 314 can provide access to the computer hardware, or can provide a single interface for common functions. Example system functions 314 include, but are not limited to, functions for establishing a service or daemon, reading an environment variable, and turning the computer system 300 off. Memory allocation functions 316 allow a caller to allocate, de-allocate, read, write, lock, or otherwise interact with the memory 310. I/O Functions 318 can allow a caller to interact with I/O devices 312. Example I/O functions include, but are not limited to, functions for establishing network sockets, writing to display buffers, and reading input from pointer devices.
The operating system can host one or more application. These application include, but are not limited to, web browsers, document editors, web servers, video games, and other applications which may or may not have user-facing components. Additionally, the operating system 304 can host one or more other execution environments. One such execution environment is the sandbox 306.
The sandbox 306 includes an execution environment for hosting one or more applications, including sandboxed applications 328 and 330. Instead of accessing the system functions 314, memory allocation 316, and I/O functions 318, the sandboxed applications 328 and 330 may be permitted only to access system hooks 322, memory hooks 324, and I/O hooks 326. In some configurations, the system hooks 322, memory hooks 324, and I/O hooks 326 may have the same interfaces as the system functions 314, memory allocation 316, and I/O functions 318 and may imitate the interfaces of the operation system 304. In some configurations, the system hooks 322, memory hooks 324, and I/O hooks 326 may have a different interface or interfaces. When making a call to a system hooks 322, memory hooks 324, or I/O hooks 326, a communication manager 320 in the sandbox 306 may examine the call and determine how to respond to the call, if at all. In some cases, the call may be passed to a corresponding system function 314, memory allocation 316, or I/O function 318. In some cases, the communication manager 320 may generate a response without communicating with the operating system. Additionally, the communication manager 320 can perform additional functions related to these calls. Calls may be logged and/or analyzed to determine, for example, if the call attempts to perform a restricted action or a permitted action on a restricted resource. The communication manager 320 may treat calls from each application 328 and 330 differently or the same, depending on the configuration.
The sandbox 306 may be used for one or more of a variety of functions. In one use, the sandbox 306 is used to provide security to the computer system 300 while the sandboxed application 328 and 330 are run. For example, the sandboxed application 328 and 330 may be from an untrusted source or may be known to have malicious behavior. By monitoring communications between the sandboxed application 328 and 330 and the operating system 304, the communication manager 320 can prevent the sandboxed application 328 and 330 from having an undesirable effect on the operating system 304.
In another use, the sandbox may be part of a virtual machine. Virtual machines are logical recreations of a full or partial computing system hosted on a real computer system like the computer system 300. Virtual machines may be used in some cases to interpret scripting language application, allowing the scripting language to be platform agnostic. Additionally or alternatively, virtual machines may be used to provision a single computer system 300 to multiple uses. For example, if the computer system 300 is a networked server computer, multiple virtual servers may be provisioned on the single real server.
In yet another use, the sandbox may be part of an emulator. Emulators are a specific type of virtual machine where the system hooks 322, memory hooks 324 and I/O hooks 326 provide a different interface than what is provided by the operating system 304. For example, a virtual machine emulating a mobile computing device may be used on a desktop computing device running a different operating system. This emulated mobile computing device may be to test an application that is developed on the desktop device but targeted for use in the mobile device.
In FIG. 3B, a sandbox modifier 350 replaces instructions in an application 352 to create a sandboxed application 354. This replacement process may be used in addition to or in the alternative to the sandbox 306 previously described.
As part of loading the application 352 for execution, a computer system can use the sandbox modifier 350 to identify and replace some of the instructions of the application 352. For binary executable applications 352, the instructions replaced include binary computer instructions. For scripted applications 352, the instructions replaced include scripting instructions.
The sandbox modifier 350 can inspect the application 352 and identify any instructions that, for example, include calls to the operating system or include calls to sensitive computing resources. In the example shown, the sandbox modifier 350 identifies two instructions, “I/O instruction4” and “Sensitive Instruction5.” Before loading the application 352, the sandbox modifier can modify the application 352 by replacing these two instructions with calls to, for example, a sandbox interface that includes hooks for function calls to the operating system. By performing such a replacement, the sandbox modifier 350 can ensure that the application 352 does not attempt to call an unauthorized function and/or “escape” the sandbox.
FIG. 4 is a flowchart of an example process 400 for testing software for signs of risk.
At 402, application signatures are identified. Each application signature represents a particular software application. Each application signature includes operations each associated with a match score. Each application signature includes a total score threshold. For example, a mobile computing device's security manager can download a pack of application signatures that each represent a particular software application found to be unwanted (e.g., malicious, containing unwanted features or security flaws).
At 404, operations performed by a software application instance executed by a computing device are monitored. For example, as the mobile computing device's operating system launches and executes applications, the operating system monitors operations performed by the software applications.
At 406, it is determined that a particular operation performed by the software application instance matches an operation included in a particular application signature. For example, the operating system may identify a Boolean expression in a signature that, for a particular operation of a software application, is found to be true.
At 408, in response to determining that the particular operation matches the operation included in the particular application signature, a match score associated with the particular operation is added to a total score associated with the software application instance. For example, the operating system may access a stored total score from a user's account in a cloud serve and add to the total score the match score. The operating system may then report the updated match score to the cloud service. Alternatively, the mobile device's operating system may report the match score, and the cloud service may compute the total score.
At 410, in response to adding the match score to the total score, it is determined that the total score for the software application instance is greater than or equal to the total score threshold for the particular application signature. In response to determining that the total score is greater than or equal to the total score threshold, the software application instance is classified as the particular software application represented by the particular application signature. For example, the mobile computing device may delete the software application, and the cloud service may generate an anonymized and/or aggregate report for a security researcher about the prevalence and behavior of the unwanted software application.
FIG. 5 is a flowchart of an example process 500 for identifying malicious application instances. In the process 500, unlike in the process 400, application signatures that identify operations to be monitored for, as well as operation sequences that specify an ordered list of operations. If tested software is found to match the operations of a signature, the weight value of those operations are added to the score for that signature. If those operations are also found to be performed in the order specified by an operation sequence, the weight of the operation sequence will also be added to the weight value for that signature. This example process will use the example signature shown above.
At 502, application signatures are identified. Each application signature represents a particular software application. Each application signature includes operations each associated with a match score, along with one or more operation sequence associated with a sequence weight. Each application signature includes a total score threshold. For example, a mobile computing device's security manager can download a pack of application signatures that each represent a particular software application found to be unwanted (e.g., malicious, containing unwanted features or security flaws).
At 504, operations performed by a software application instance executed by a computing device are monitored. For example, as the mobile computing device's operating system launches and executes applications, the operating system monitors operations performed by the software applications. In this example, the operating system launches an application that attempts to modify a system library. This activity can be identified as matching the “libraries” event in the signature shown above, for a match score of 1.
At 506, operation sequences are matched. At this time, the only operations matched is the “libraries” event, which, on its own, does not match any of the operation sequences. At 508, the match score is calculated. Currently, the match score is 1, and control returns to element 504.
At 504, operations performed by a software application instance executed by a computing device are monitored. The activity of the application is further monitored, and actions taken by the software to change the registry are identified as “registryKeys,” for a match score of 1. At 506, it is determined that the sequence of “libraries” followed “registryKeys” matches the operation sequence “Targeting system files,” for an additional sequence weight of 3.
At 510 and 512, the total score of 5 is found (e.g. 1+1+3) and compared to the “matchTotalScore” for the signature, which is a value of 3. As the total score of 5 is greater than or equal to 3, the software is identifies as matching this signature.
FIG. 6 is a schematic diagram that shows an example of a computing system 600. The computing system 600 can be used for some or all of the operations described previously, according to some implementations. The computing system 600 includes a processor 610, a memory 620, a storage device 630, and an input/output device 640. Each of the processor 610, the memory 620, the storage device 630, and the input/output device 640 are interconnected using a system bus 650. The processor 610 is capable of processing instructions for execution within the computing system 600. In some implementations, the processor 610 is a single-threaded processor. In some implementations, the processor 610 is a multi-threaded processor. The processor 610 is capable of processing instructions stored in the memory 620 or on the storage device 630 to display graphical information for a user interface on the input/output device 640.
The memory 620 stores information within the computing system 600. In some implementations, the memory 620 is a computer-readable medium. In some implementations, the memory 620 is a volatile memory unit. In some implementations, the memory 620 is a non-volatile memory unit.
The storage device 630 is capable of providing mass storage for the computing system 600. In some implementations, the storage device 630 is a computer-readable medium. In various different implementations, the storage device 630 may be a floppy disk device, a hard disk device, an optical disk device, or a tape device.
The input/output device 640 provides input/output operations for the computing system 600. In some implementations, the input/output device 640 includes a keyboard and/or pointing device. In some implementations, the input/output device 640 includes a display unit for displaying graphical user interfaces.
Some features described can be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations of them. The apparatus can be implemented in a computer program product tangibly embodied in an information carrier, e.g., in a machine-readable storage device, for execution by a programmable processor; and method steps can be performed by a programmable processor executing a program of instructions to perform functions of the described implementations by operating on input data and generating output. The described features can be implemented advantageously in one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from, and to transmit data and instructions to, a data storage system, at least one input device, and at least one output device. A computer program is a set of instructions that can be used, directly or indirectly, in a computer to perform a certain activity or bring about a certain result. A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.
Suitable processors for the execution of a program of instructions include, by way of example, both general and special purpose microprocessors, and the sole processor or one of multiple processors of any kind of computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for executing instructions and one or more memories for storing instructions and data. Generally, a computer will also include, or be operatively coupled to communicate with, one or more mass storage devices for storing data files; such devices include magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and optical disks. Storage devices suitable for tangibly embodying computer program instructions and data include all forms of non-volatile memory, including by way of example semiconductor memory devices, such as EPROM (erasable programmable read-only memory), EEPROM (electrically erasable programmable read-only memory), and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM (compact disc read-only memory) and DVD-ROM (digital versatile disc read-only memory) disks. The processor and the memory can be supplemented by, or incorporated in, ASICs (application-specific integrated circuits).
To provide for interaction with a user, some features can be implemented on a computer having a display device such as a CRT (cathode ray tube) or LCD (liquid crystal display) monitor for displaying information to the user and a keyboard and a pointing device such as a mouse or a trackball by which the user can provide input to the computer.
Some features can be implemented in a computer system that includes a back-end component, such as a data server, or that includes a middleware component, such as an application server or an Internet server, or that includes a front-end component, such as a client computer having a graphical user interface or an Internet browser, or any combination of them. The components of the system can be connected by any form or medium of digital data communication such as a communication network. Examples of communication networks include, e.g., a LAN (local area network), a WAN (wide area network), and the computers and networks forming the Internet.
The computer system can include clients and servers. A client and server are generally remote from each other and typically interact through a network, such as the described one. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
This document describes technologies that can be applied to a wide range of uses, which are designed and intended to be beneficial for all users involved. However, some of the technologies described may be put to illegitimate, malicious, and even illegal ends by bad actors. This is true with almost any technology, but there is often a greater sensitivity when a technology interacts with a user's security and private information. The described technologies all are designed to operate in an environment and in a manner that respects the rights of all users. As such, features such as user notification, opt-in and opt-out procedures, and privacy settings are available options to be used to ensure user security and privacy are respected.

Claims (30)

What is claimed is:
1. A method performed by data processing apparatus, the method comprising:
identifying application signatures each representing one or more software applications, each application signature including a total score threshold and one or more sequence listing each including a plurality of sequence operations, wherein each sequence listing is associated with a sequence score;
monitoring operations performed by a software application instance executed by a computing device;
determining that a first operation performed by the software application instance matches a first sequence operation included in a particular sequence listing for a particular application signature;
after determining that the first operation performed by the software application instance matches the first sequence operation, determining that a second operation performed by the software application instance matches a second sequence operation included in the particular sequence listing;
in response to determining that the second operation matches the second sequence operation, determining that each of the plurality of sequence operations for the particular sequence listing has been observed for the software application instance;
in response to determining that each of the plurality of sequence operations for the particular sequence listing has been observed, adding the sequence score to a total score for the software application instance;
in response to adding the sequence score to the total score, determining that the total score for the software application instance is greater than or equal to the total score threshold for the particular application signature; and
in response to determining that the total score is greater than or equal to the total score threshold, classifying the software application instance as the software application represented by the particular application signature.
2. The method of claim 1, wherein each application signature includes operations each associated with a match score, and the method further comprises:
determining that the first particular operation performed by the software application instance matches an operation included in the particular application signature; and
in response to determining that the first particular operation matches the operation included in the particular application signature, adding a match score associated with the particular operation to the total score associated with the software application instance.
3. The method of claim 1, wherein the sequence listing includes a particular order for the plurality of sequence operations, the first sequence operation being in a first position in the particular order, and the second sequence operation being in a final position in the particular order.
4. The method of claim 1, wherein monitoring operations performed by a software application instance executed by a computing device comprises:
performing static analysis of one or more attributes of the software application instance.
5. The method of claim 4, wherein performing static analysis of one or more attributes of the software application instance comprises:
determining if the one or more attributes match a preconfigured value in an application signature.
6. The method of claim 5, wherein the one or more attributes includes at least one of the group consisting of a Secure Hash Algorithm (SHA) value, an MD5 value, and a program name.
7. The method of claim 1, the method further comprising performing, responsive to classifying the software application instance as the software application represented by the particular application signature, a configured action associated with the particular application signature.
8. The method of claim 7, wherein the configured action is selected from a plurality of actions based on a determination of a type of the computing device.
9. The method of claim 8, wherein the determined type is a network security device; and the configured action comprises terminating network traffic with a server that served the software application.
10. The method of claim 8, wherein the determined type is a client device that resides on a network; and the configured action comprises powering down the client device.
11. The method of claim 7, wherein the configured action comprises presenting, responsive to classifying the software application instance as the software application represented by the particular application signature, a report identifying i) the software application and ii) the particular application signature.
12. The method of claim 11, wherein the report further comprises a human-readable description of the particular application signature.
13. The method of claim 11, the method further comprising generating the report from a template document that includes at least an application-related fillable field and a signature-related fillable field using data associated with the particular application signature.
14. The method of claim 1, wherein the software application instance executed by a computing device is executed on a client device.
15. The method of claim 1, wherein the software application instance executed by a computing device is executed in a sandbox environment.
16. The method of claim 1, wherein each application signature represents a particular class of software application include the one or more software applications.
17. The method of claim 1, the method further comprising:
monitoring operations performed by a second software application instance executed by the computing device;
determining that a particular operation performed by the second software application instance matches an operation included in the particular application signature;
in response to determining that the particular operation matches the operation included in the particular application signature, adding a match score associated with the particular operation to a total score associated with the second software application instance;
in response to adding the match score to the total score, determining that the total score for the software application instance is less than the total score threshold for the particular application signature; and
in response to determining that the total score is greater than or equal to the total score threshold, allowing the second software application instance to continue execution without classifying it as the software application.
18. A system comprising:
one or more processors configured to execute computer program instructions; and
non-transitory computer storage media encoded with computer program instructions that, when executed by one or more processors, cause a computer device to perform operations comprising:
identifying application signatures each representing one or more software applications, each application signature including a total score threshold and one or more sequence listing each including a plurality of sequence operations, wherein each sequence listing is associated with a sequence score;
monitoring operations performed by a software application instance executed by a computing device;
determining that a first operation performed by the software application instance matches a first sequence operation included in a particular sequence listing for a particular application signature;
after determining that the first operation performed by the software application instance matches the first sequence operation, determining that a second operation performed by the software application instance matches a second sequence operation included in the particular sequence listing;
in response to determining that the second operation matches the second sequence operation, determining that each of the plurality of sequence operations for the particular sequence listing has been observed for the software application instance;
in response to determining that each of the plurality of sequence operations for the particular sequence listing has been observed, adding the sequence score to a total score for the software application instance;
in response to adding the sequence score to the total score, determining that the total score for the software application instance is greater than or equal to the total score threshold for the particular application signature; and
in response to determining that the total score is greater than or equal to the total score threshold, classifying the software application instance as the software application represented by the particular application signature.
19. The system of claim 18, wherein monitoring operations performed by a software application instance executed by a computing device comprises:
performing static analysis of one or more attributes of the software application instance.
20. The system of claim 19, wherein performing static analysis of one or more attributes of the software application instance comprises:
determining if the one or more attributes match a preconfigured value in an application signature.
21. The system of claim 18, wherein the operations further comprise performing, responsive to classifying the software application instance as the software application represented by the particular application signature, a configured action associated with the particular application signature.
22. The system of claim 21, wherein the configured action is selected from a plurality of actions based on a determination of a type of the computing device.
23. The system of claim 21, wherein the configured action comprises presenting, responsive to classifying the software application instance as the software application represented by the particular application signature, a report identifying i) the software application and ii) the particular application signature.
24. The system of claim 23, wherein the report further comprises a human-readable description of the particular application signature.
25. The system of claim 23, wherein the operations further comprise generating the report from a template document that includes at least an application-related fillable field and a signature-related fillable field using data associated with the particular application signature.
26. The system of claim 18, wherein the software application instance execute by a computing device is executed on a client device.
27. The system of claim 18, wherein the software application instance executed by a computing device is executed in a sandbox environment.
28. The system of claim 18, wherein each application signature represents a particular class of software application include the one or more software applications.
29. The system of claim 18, wherein the operations further comprise:
monitoring operations performed by a second software application instance executed by the computing device;
determining that a particular operation performed by the second software application instance matches an operation included in the particular application signature;
in response to determining that the particular operation matches the operation included in the particular application signature, adding a match score associated with the particular operation to a total score associated with the second software application instance;
in response to adding the match score to the total score, determining that the total score for the software application instance is less than the total score threshold for the particular application signature; and
in response to determining that the total score is greater than or equal to the total score threshold, allowing the second software application instance to continue execution without classifying it as the software application.
30. A non-transitory computer storage media encoded with computer program instructions that, when executed by one or more processors, cause a computer device to perform operations comprising:
identifying application signatures each representing one or more software applications, each application signature including a total score threshold and one or more sequence listing each including a plurality of sequence operations, wherein each sequence listing is associated with a sequence score;
monitoring operations performed by a software application instance executed by a computing device;
determining that a first operation performed by the software application instance matches a first sequence operation included in a particular sequence listing for a particular application signature;
after determining that the first operation performed by the software application instance matches the first sequence operation, determining that a second operation performed by the software application instance matches a second sequence operation included in the particular sequence listing;
in response to determining that the second operation matches the second sequence operation, determining that each of the plurality of sequence operations for the particular sequence listing has been observed for the software application instance;
in response to determining that each of the plurality of sequence operations for the particular sequence listing has been observed, adding the sequence score to a total score for the software application instance;
in response to adding the sequence score to the total score, determining that the total score for the software application instance is greater than or equal to the total score threshold for the particular application signature; and
in response to determining that the total score is greater than or equal to the total score threshold, classifying the software application instance as the software application represented by the particular application signature.
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Cited By (25)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107172035A (en) * 2017-05-11 2017-09-15 北京安赛创想科技有限公司 The detection method and device of network attack information
US20180007068A1 (en) * 2016-07-01 2018-01-04 Mcafee, Inc. System and method to detect bypass of a sandbox application
CN109325003A (en) * 2018-09-27 2019-02-12 维沃移动通信有限公司 A kind of application program classifying method and system based on terminal device
CN109684826A (en) * 2018-01-15 2019-04-26 北京微步在线科技有限公司 Anti- method and the electronic equipment of escaping of application program sandbox
US10289536B2 (en) * 2016-08-31 2019-05-14 Synopsys, Inc. Distinguishing public and private code in testing environments
CN110537181A (en) * 2017-03-01 2019-12-03 赛门铁克公司 Manage data encryption application program
US10785028B2 (en) * 2018-06-29 2020-09-22 Intel Corporation Protection of keys and sensitive data from attack within microprocessor architecture
US10873588B2 (en) * 2017-08-01 2020-12-22 Pc Matic, Inc. System, method, and apparatus for computer security
US10990759B1 (en) * 2018-07-31 2021-04-27 Amazon Technologies, Inc. Deviation-based framework
US11055403B2 (en) 2017-01-06 2021-07-06 International Business Machines Corporation Method, system, and computer program product for application identification in a cloud platform
US11070581B1 (en) * 2017-08-24 2021-07-20 Wells Fargo Bank, N.A. Eliminating network security blind spots
US11354464B2 (en) * 2016-09-27 2022-06-07 Google Llc Selective simulation of virtualized hardware inputs
US20220198024A1 (en) * 2020-12-22 2022-06-23 Microsoft Technology Licensing, Llc. Correlation between source code repositories and web endpoints
US20220269785A1 (en) * 2021-02-23 2022-08-25 Saudi Arabian Oil Company Enhanced cybersecurity analysis for malicious files detected at the endpoint level
US11431676B2 (en) * 2015-12-24 2022-08-30 Huawei Technologies Co., Ltd. Method, apparatus, and system for detecting terminal security status
US20220276860A1 (en) * 2021-02-26 2022-09-01 Open Weaver Inc. Methods and systems for automated open source software reuse scoring
US11609984B2 (en) * 2018-02-14 2023-03-21 Digital Guardian Llc Systems and methods for determining a likelihood of an existence of malware on an executable
US11704589B1 (en) * 2017-03-20 2023-07-18 Amazon Technologies, Inc. Automatically identifying dynamic applications
US11782826B2 (en) 2020-02-13 2023-10-10 Intel Corporation Security check systems and methods for memory allocations
US11836069B2 (en) 2021-02-24 2023-12-05 Open Weaver Inc. Methods and systems for assessing functional validation of software components comparing source code and feature documentation
US11836202B2 (en) 2021-02-24 2023-12-05 Open Weaver Inc. Methods and systems for dynamic search listing ranking of software components
US11893385B2 (en) 2021-02-17 2024-02-06 Open Weaver Inc. Methods and systems for automated software natural language documentation
US11921763B2 (en) 2021-02-24 2024-03-05 Open Weaver Inc. Methods and systems to parse a software component search query to enable multi entity search
US11947530B2 (en) 2021-02-24 2024-04-02 Open Weaver Inc. Methods and systems to automatically generate search queries from software documents to validate software component search engines
US11954045B2 (en) 2021-09-24 2024-04-09 Intel Corporation Object and cacheline granularity cryptographic memory integrity

Families Citing this family (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9954880B2 (en) * 2015-10-30 2018-04-24 Salesforce.Com, Inc. Protection via webpage manipulation
US10757205B2 (en) * 2016-08-17 2020-08-25 Performance And Privacy Ireland Ltd. Deriving mobile application usage from network traffic
US9876753B1 (en) 2016-12-22 2018-01-23 Wombat Security Technologies, Inc. Automated message security scanner detection system
US10534909B2 (en) * 2017-03-02 2020-01-14 Fortinet, Inc. Multi-tiered sandbox based network threat detection
US11601467B2 (en) 2017-08-24 2023-03-07 L3 Technologies, Inc. Service provider advanced threat protection
US11552987B2 (en) * 2017-09-28 2023-01-10 L3 Technologies, Inc. Systems and methods for command and control protection
US11550898B2 (en) 2017-10-23 2023-01-10 L3 Technologies, Inc. Browser application implementing sandbox based internet isolation
US11308218B2 (en) 2018-12-20 2022-04-19 Visa International Service Association Open source vulnerability remediation tool
US10630715B1 (en) 2019-07-25 2020-04-21 Confluera, Inc. Methods and system for characterizing infrastructure security-related events
US10630716B1 (en) 2019-07-25 2020-04-21 Confluera, Inc. Methods and system for tracking security risks over infrastructure
US10630704B1 (en) 2019-07-25 2020-04-21 Confluera, Inc. Methods and systems for identifying infrastructure attack progressions
US10630703B1 (en) 2019-07-25 2020-04-21 Confluera, Inc. Methods and system for identifying relationships among infrastructure security-related events
US10574683B1 (en) * 2019-07-25 2020-02-25 Confluera, Inc. Methods and system for detecting behavioral indicators of compromise in infrastructure
US10887337B1 (en) 2020-06-17 2021-01-05 Confluera, Inc. Detecting and trail-continuation for attacks through remote desktop protocol lateral movement
US11853425B2 (en) * 2020-10-09 2023-12-26 Sophos Limited Dynamic sandbox scarecrow for malware management
US11429515B1 (en) * 2021-05-13 2022-08-30 Arm Limited Monitoring execution of software using path signature
US11831688B2 (en) * 2021-06-18 2023-11-28 Capital One Services, Llc Systems and methods for network security
US11599637B1 (en) * 2021-07-30 2023-03-07 Cloud Linux Software, Inc. Systems and methods for blocking malicious script execution
US20230049789A1 (en) * 2021-07-30 2023-02-16 Cloud Linux Software Inc. Systems and methods for preventing zero-day attacks
US11397808B1 (en) 2021-09-02 2022-07-26 Confluera, Inc. Attack detection based on graph edge context

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040042642A1 (en) * 1999-12-02 2004-03-04 International Business Machines, Corporation System and method for distortion characterization in fingerprint and palm-print image sequences and using this distortion as a behavioral biometrics
US20100058473A1 (en) * 2008-08-28 2010-03-04 Avg Technologies Cz, S.R.O. Heuristic method of code analysis
US7779472B1 (en) 2005-10-11 2010-08-17 Trend Micro, Inc. Application behavior based malware detection
US8010522B2 (en) * 2007-12-07 2011-08-30 International Business Machines Corporation System, method and program product for detecting SQL queries injected into data fields of requests made to applications
US8370931B1 (en) 2008-09-17 2013-02-05 Trend Micro Incorporated Multi-behavior policy matching for malware detection
US8555385B1 (en) 2011-03-14 2013-10-08 Symantec Corporation Techniques for behavior based malware analysis
US8776218B2 (en) 2009-07-21 2014-07-08 Sophos Limited Behavioral-based host intrusion prevention system

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7450005B2 (en) * 2006-01-18 2008-11-11 International Business Machines Corporation System and method of dynamically weighted analysis for intrusion decision-making
US9015843B2 (en) * 2010-12-03 2015-04-21 Microsoft Corporation Predictive malware threat mitigation
US9154516B1 (en) * 2013-09-27 2015-10-06 Emc Corporation Detecting risky network communications based on evaluation using normal and abnormal behavior profiles
US9319430B2 (en) * 2014-06-17 2016-04-19 International Business Machines Corporation Managing software deployment
US9294492B1 (en) * 2015-03-10 2016-03-22 Iboss, Inc. Software program identification based on program behavior

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040042642A1 (en) * 1999-12-02 2004-03-04 International Business Machines, Corporation System and method for distortion characterization in fingerprint and palm-print image sequences and using this distortion as a behavioral biometrics
US7779472B1 (en) 2005-10-11 2010-08-17 Trend Micro, Inc. Application behavior based malware detection
US8010522B2 (en) * 2007-12-07 2011-08-30 International Business Machines Corporation System, method and program product for detecting SQL queries injected into data fields of requests made to applications
US20100058473A1 (en) * 2008-08-28 2010-03-04 Avg Technologies Cz, S.R.O. Heuristic method of code analysis
US8370931B1 (en) 2008-09-17 2013-02-05 Trend Micro Incorporated Multi-behavior policy matching for malware detection
US8776218B2 (en) 2009-07-21 2014-07-08 Sophos Limited Behavioral-based host intrusion prevention system
US8555385B1 (en) 2011-03-14 2013-10-08 Symantec Corporation Techniques for behavior based malware analysis

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
Hofmeyr, Steven A., Stephanie Forrest, and Anil Somayaji. "Intrusion detection using sequences of system calls." Journal of computer security 6.3 (1998): 151-180. *
Preda, "A Semantics-Based Approach to Malware Detection", 2007, downloaded from the internet at http://www.cs.arizona.edu/~debray/Publications/semantic-malware.pdf on Jun. 26, 2015, 12 pages.
Preda, "A Semantics-Based Approach to Malware Detection", 2007, downloaded from the internet at http://www.cs.arizona.edu/˜debray/Publications/semantic-malware.pdf on Jun. 26, 2015, 12 pages.

Cited By (33)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11431676B2 (en) * 2015-12-24 2022-08-30 Huawei Technologies Co., Ltd. Method, apparatus, and system for detecting terminal security status
US20180007068A1 (en) * 2016-07-01 2018-01-04 Mcafee, Inc. System and method to detect bypass of a sandbox application
US10574672B2 (en) * 2016-07-01 2020-02-25 Mcafee, Llc System and method to detect bypass of a sandbox application
US10289536B2 (en) * 2016-08-31 2019-05-14 Synopsys, Inc. Distinguishing public and private code in testing environments
US11354464B2 (en) * 2016-09-27 2022-06-07 Google Llc Selective simulation of virtualized hardware inputs
US11055403B2 (en) 2017-01-06 2021-07-06 International Business Machines Corporation Method, system, and computer program product for application identification in a cloud platform
CN110537181A (en) * 2017-03-01 2019-12-03 赛门铁克公司 Manage data encryption application program
CN110537181B (en) * 2017-03-01 2023-07-28 Ca公司 Method for classifying application data, computing device and storage medium
US11704589B1 (en) * 2017-03-20 2023-07-18 Amazon Technologies, Inc. Automatically identifying dynamic applications
CN107172035A (en) * 2017-05-11 2017-09-15 北京安赛创想科技有限公司 The detection method and device of network attack information
US10873588B2 (en) * 2017-08-01 2020-12-22 Pc Matic, Inc. System, method, and apparatus for computer security
US11070581B1 (en) * 2017-08-24 2021-07-20 Wells Fargo Bank, N.A. Eliminating network security blind spots
US11824887B1 (en) * 2017-08-24 2023-11-21 Wells Fargo Bank, N.A. Eliminating network security blind spots
CN109684826A (en) * 2018-01-15 2019-04-26 北京微步在线科技有限公司 Anti- method and the electronic equipment of escaping of application program sandbox
US11609984B2 (en) * 2018-02-14 2023-03-21 Digital Guardian Llc Systems and methods for determining a likelihood of an existence of malware on an executable
US20200382303A1 (en) * 2018-06-29 2020-12-03 Intel Corporation Protection of keys and sensitive data from attack within microprocessor architecture
US11838418B2 (en) * 2018-06-29 2023-12-05 Intel Corporation Protection of keys and sensitive data from attack within microprocessor architecture
US10785028B2 (en) * 2018-06-29 2020-09-22 Intel Corporation Protection of keys and sensitive data from attack within microprocessor architecture
US10990759B1 (en) * 2018-07-31 2021-04-27 Amazon Technologies, Inc. Deviation-based framework
CN109325003A (en) * 2018-09-27 2019-02-12 维沃移动通信有限公司 A kind of application program classifying method and system based on terminal device
US11782826B2 (en) 2020-02-13 2023-10-10 Intel Corporation Security check systems and methods for memory allocations
US20220198024A1 (en) * 2020-12-22 2022-06-23 Microsoft Technology Licensing, Llc. Correlation between source code repositories and web endpoints
US11657161B2 (en) * 2020-12-22 2023-05-23 Microsoft Technology Licensing, Llc. Correlation between source code repositories and web endpoints
US11893385B2 (en) 2021-02-17 2024-02-06 Open Weaver Inc. Methods and systems for automated software natural language documentation
US20220269785A1 (en) * 2021-02-23 2022-08-25 Saudi Arabian Oil Company Enhanced cybersecurity analysis for malicious files detected at the endpoint level
US11836069B2 (en) 2021-02-24 2023-12-05 Open Weaver Inc. Methods and systems for assessing functional validation of software components comparing source code and feature documentation
US11836202B2 (en) 2021-02-24 2023-12-05 Open Weaver Inc. Methods and systems for dynamic search listing ranking of software components
US11921763B2 (en) 2021-02-24 2024-03-05 Open Weaver Inc. Methods and systems to parse a software component search query to enable multi entity search
US11947530B2 (en) 2021-02-24 2024-04-02 Open Weaver Inc. Methods and systems to automatically generate search queries from software documents to validate software component search engines
US20220276860A1 (en) * 2021-02-26 2022-09-01 Open Weaver Inc. Methods and systems for automated open source software reuse scoring
US11853745B2 (en) * 2021-02-26 2023-12-26 Open Weaver Inc. Methods and systems for automated open source software reuse scoring
US11954045B2 (en) 2021-09-24 2024-04-09 Intel Corporation Object and cacheline granularity cryptographic memory integrity
US11960492B2 (en) 2022-02-23 2024-04-16 Open Weaver Inc. Methods and systems for display of search item scores and related information for easier search result selection

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